Detection of surface contamination

Abstract

A device implements a method for detecting contamination of an FTIR-based panel. The apparatus generates projection signals representing detection lines that have propagated on a plurality of propagation paths by total internal reflection (TIR) inside a transmissive panel such that contamination on the panel surface causes attenuation (frustration) of at least one of the projection signals. The device generates a transmission value for each detection line in the transmissive panel, and determines the presence of contamination on the surface of the panel by comparing the transmission values according to at least one of the presented comparison techniques.

Claims

1. A system for detecting surface contamination on a touch screen apparatus, comprising: a light transmissive element that defines a surface; a set of emitters arranged to emit beams of light into the light transmissive element, wherein the beams of light propagate inside the light transmissive element while illuminating the surface such that surface contamination on the surface causes an attenuation of the propagating light, a set of light detectors arranged proximal to the surface to receive light from the set of emitters on a plurality of light paths, and a hardware processor configured to: determine, based on output signals from the light detectors, a transmission value for each light path in the plurality of light paths; determine a first group transmission value for a first plurality of light paths in the plurality of light paths, wherein the first plurality of light paths share a first property; determine a second group transmission value for a second plurality of lights in the plurality of light paths, wherein the second plurality of light paths share a second property different from the first property; generate a contamination value based on the first group transmission value with the second group transmission value; and display an indication of surface contamination based on the generated contamination value.

2. The system of claim 1, wherein the first group transmission value comprises a lowest transmission value of all transmission values corresponding to respective first plurality of light paths and wherein the second group transmission value comprises a highest transmission value of all transmission values corresponding to respective second plurality of light paths.

3. The system of claim 1, wherein the first group transmission value comprises an average value of all transmission values corresponding to respective first plurality of light paths and wherein the second group transmission value comprises an average value of all transmission values corresponding to respective second plurality of light paths.

4. The system of claim 1, wherein the first and second plurality of light paths comprise light paths with an angle within 40 degrees of any other member of their respective set.

5. The system of claim 1, wherein the first and second plurality of light paths comprise light paths having a length with a maximum variance of 10% from the length of any other member of their respective set.

6. The system of claim 1, wherein the first property comprises a first average length of light paths in the first plurality of light paths and the second property comprises a second average length of light paths in the second plurality of light paths, wherein the first average length is longer than the second average length.

7. The system of claim 1, wherein the first property comprises all light paths originating from the same emitter.

8. The system of claim 1, wherein the second property comprises all light paths originating from the same emitter.

9. The system of claim 1, wherein the indication of surface contamination is determined based on a comparison of the generated contamination value with a predetermined threshold.

10. The system of claim 1, wherein the first plurality of light paths are substantially perpendicular to the second plurality of light paths.

11. The system of claim 1, wherein is the contamination value is based on a ratio between the first group transmission value and the second group transmission value.

12. The system of claim 11, wherein the hardware processor is further configured to: determine a map of a surface contamination on at least a portion of the surface.

13. The system of claim 12, wherein the map of the surface contamination on at least a portion of the surface is generated based on a back-projection of a plurality of transmission variance values onto the map.

14. A method for determining contamination in a contamination detecting apparatus, said contamination detecting apparatus comprising: a light transmissive element that defines a surface; a set of emitters arranged to emit beams of light into the light transmissive element wherein the beams of light propagate inside the light transmissive element while illuminating the surface such that surface contamination on the surface causes an attenuation of the propagating light; and a set of light detectors arranged proximal to the surface to receive light from the set of emitters on a plurality of light paths; said method comprising: determining, based on output signals from the light detectors, a transmission value for each light path in the plurality of light paths; determining a first group transmission value for a first set of light paths in the plurality of light paths, wherein the first set of light paths share a first property; determining a second group transmission value for a second set of lights in the plurality of light paths, wherein the second set of light paths share a second property; generating a contamination value based on the first group transmission value with the second group transmission value; and displaying an indication of surface contamination based on the generated contamination value.

15. A non-transitory, tangible computer readable storage medium storing processing instructions that, when executed by a hardware processor, performs the method according to claim 14.

Description

BRIEF DESCRIPTION OF DRAWINGS

(1) Embodiments of the invention will now be described in more detail with reference to the accompanying schematic drawings.

(2) FIGS. 1a-1b are section and top plan views of an FTIR-based system of projection-type.

(3) FIG. 2 is a flowchart of a data extraction process in the system of FIG. 1.

(4) FIG. 3 is a flowchart of a global contamination detection process.

(5) FIG. 4a-4b illustrate a globally contaminated panel and the detection lines used to detect the global contamination.

(6) FIG. 5 is a flowchart of a regional contamination detection process.

(7) FIGS. 6a-6f a regionally contaminated panel and the detection lines used to detect the regional contamination.

(8) FIGS. 7a-7c show user interface configurations to alert the user to the presence, type, and location of the contamination.

(9) FIG. 8 shows an example of a data processing device.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

(10) Throughout the following description, the same reference numerals are used to identify corresponding elements.

(11) Panel

(12) FIGS. 1A-1B illustrate an example embodiment of a surface contamination detection apparatus 100 that is based on the concept of FTIR (Frustrated Total Internal Reflection), also denoted FTIR system. The apparatus operates by transmitting light inside a panel 1, from light emitters 2 to light sensors or detectors 3, so as to illuminate a surface 4 from within the panel 1. The panel 1 is made of solid material in one or more layers and may have any shape. The panel 1 defines an internal radiation propagation channel, in which light propagates by internal reflections. In the example of FIG. 1, the propagation channel is defined between the boundary surfaces 4, 5 of the panel 1, where the top surface 4 allows the propagating light to interact with contamination 7. This is achieved by injecting the light into the panel 1 such that the light is reflected by total internal reflection (TIR) in the surface 4 as it propagates through the panel 1. The light may be reflected by TIR in the bottom surface 5 or against a reflective coating thereon. It is also conceivable that the propagation channel is spaced from the bottom surface 5, e.g. if the panel comprises multiple layers of different materials.

(13) Attenuation

(14) The apparatus 100 allows surface contamination 7 that is in contact with the surface 4 to interact with the propagating light. In this interaction, part of the light may be scattered by the surface contamination 7, part of the light may be absorbed by the surface contamination 7, and part of the light may continue to propagate in its original direction across the panel 1. Thus, the surface contamination 7 causes a local frustration of the total internal reflection, which leads to a decrease in the energy (power/intensity) of the transmitted light, as indicated by the thinned lines downstream of the surface contamination 7 in FIG. 1A.

(15) Emitters

(16) The emitters 2 are distributed along the perimeter of the surface 4 to generate a corresponding number of light sheets inside the panel 1. In the example of FIG. 1B, each emitter 2 generates a beam of light that expands in the plane of the panel 1 while propagating in the panel 1. Each beam propagates from one or more entry or incoupling points on the panel 1.

(17) Detectors

(18) The sensors 3 are distributed along the perimeter of the surface 4 to receive the light from the emitters 2 at a number of spaced-apart outcoupling points on the panel 1. It should be understood that the incoupling and outcoupling points merely refer to the position where the beam enters and leaves, respectively, the panel 1. Thus, one emitter/sensor may be optically coupled to a number of incoupling/outcoupling points. As used herein, a detection line is defined as the line extending from one incoupling point to one outcoupling point. In the example of FIG. 1B, however, the detection lines D are defined by individual emitter-sensor pairs.

(19) Signal Processor

(20) The sensors 3 collectively provide an output signal, which is received and sampled by a signal processor 10. The output signal contains a number of sub-signals, also denoted projection signals, each representing the energy of light emitted by a certain light emitter 2 and received by a certain light sensor 3. The signal processor 10 may need to process the output signal for separation of the individual projection signals. Conceptually, the apparatus 100 is considered to define a grid of detection lines D on the surface 4, where each detection line D corresponds to a light propagation path from an emitter 2 to a sensor 3, as projected onto the surface 4. Thus, the projection signals represent the received energy or power of light on the individual detection lines D. It is realized that the surface contamination 7 results in a decrease (attenuation) of the received energy on one or more detection lines D.

(21) As will be explained below, the signal processor 10 may be configured to process the projection signals to provide transmission values which may then be used to determine one or more variances in the attenuation of the individual signals. The variances can then be processed according to the algorithms of the present invention to determine a surface contamination of the panel surface 4.

(22) Controller

(23) In the illustrated example, the apparatus 100 also includes a controller 12 which is connected to selectively control the activation of the emitters 2 and, possibly, the readout of data from the sensors 3. The signal processor 10 and the controller 12 may be configured as separate units, or they may be incorporated in a single unit. One or both of the signal processor 10 and the controller 12 may be at least partially implemented by software executed by a processing unit 14.

(24) Similar Sequence Methods

(25) It is to be understood that FIGS. 1a and 1b merely illustrates one example of an FTIR system. For example, the detection lines may instead be generated by sweeping or scanning one or more beams of light inside the panel 1, and the light may instead be coupled into and out of the panel 1 via the top and bottom surfaces 4, 5, e.g. by the use of dedicated coupling elements attached to the panel 1. Prior art documents disclosing alternative FTIR systems are listed in the Background section, all of which are incorporated herein by this reference. The inventive concept may be applied to such alternative FTIR systems as well.

(26) Data Extraction Process

(27) FIG. 2 is a flow chart of a contamination detection process in an FTIR system. The process involves a sequence of steps 20-23 that are repeatedly executed, e.g. by the signal processor 10 (FIG. 1). In the context of this description, each sequence of steps 20-23 is denoted a frame or an iteration.

(28) Each frame starts by a data collection step 20, in which measurement values are obtained from the light sensors 3 in the FTIR system, typically by sampling a value from each of the aforesaid projection signals. The data collection step 20 results in one transmission value for each detection line. It may be noted that the data may, but need not, be collected for all available detection lines in the FTIR system. The data collection step 20 may also include pre-processing of the measurement values, e.g. filtering for noise reduction, normalisation with a respective reference value, applying a logarithm on each measurement value.

(29) In step 21, a determination of a global contamination on the surface of panel 1 of the FTIR system is performed according to the methods described below. In step 22, a determination of the regional contamination of the surface of panel 1 of the FTIR system is performed according to the methods described below. In step 23, the contamination handling module receives the measured global and regional contamination values and operates to perform a response e.g. notify the user of a detected contamination.

(30) In other embodiments, global contamination detection or regional contamination detection may be performed on its own, i.e. either step 21 or step 22 would be omitted. In another embodiment, step 21 and step 22 are reversed.

(31) Surface Contamination Detection Algorithm

(32) Below are described two methods of determining contamination on the surface of the panel.

(33) Global Contamination Determination

(34) FIG. 3 is a flow chart of a global contamination detection process in an FTIR system. The process involves a sequence of steps 310-350 that are executed each time a determination of global contamination on the panel is required. In this case, a measure of the global contamination is defined as a single measure indicating the amount of contamination covering the surface. This can therefore be used to indicate total contamination regardless of whether the contamination is localized or is spread across the entire surface of the panel. An example of contamination covering the entire surface may be dust and grime collected over a long period of time, fine water droplets dispersed across the panel from rain or other sources, etc.

(35) To determine a value of the total contamination level on the panel, two techniques are presented. These two techniques may be used individually or independently to determine a global contamination level or may be combined to produce a more accurate value of the global contamination level.

(36) The first technique makes use of the fact that, on average, long detection lines will pass through more contamination than short ones. Consequently, longer detection lines are likely to be more attenuated than short ones. All detection lines suffer from a degree of attenuation due to bulk absorption i.e. absorption of the light by the glass itself. However, for a clean panel, the transmission value for a long detection line will be only slightly less than the corresponding transmission value for a short detection line. However, for a contaminated panel, the difference between the transmission value for the long detection line and the transmission value for the short detection line will increase. For a heavily contaminated panel, the difference between the transmission values is significant. Consequently, a measure of the differences in transmission values between long and short detection lines can provide a determination of the contamination in the areas crossed by the detection lines. This technique gives particularly good estimation of attenuation of the panel when the panel is uniformly contaminated.

(37) The second technique makes use of the fact that contamination is rarely completely uniform. The transmission values are compared for a set of detection lines that have approximately the same transmission value when the panel is clean. By determining a ratio between strongest and weakest transmission values of the compared detection lines, a determination of contamination of the panel can be made. i.e. The variation between the strongest and weakest detection lines (i.e. the detection lines with the strongest and weakest transmission values) increases as the contamination has a random effect on the attenuation of the detection lines. The strongest line from this subset will be the detection line that goes through the least amount of contamination and the weakest line will go through the most amount of contamination. As the ratio between the strongest and weakest transmission value rises, the probability of the presence of contamination in the region which the lines pass through is increased

(38) In a preferred embodiment, a combination of the two techniques is employed. In the preferred embodiment, the maximum transmission values for a set of short detection lines is compared to the minimum transmission values for a set of long detection lines. This combination of the presented techniques becomes even more suitable for determining the global contamination level. The maximum transmission value of a relatively large set of short detection lines is the detection line that has been attenuated by the least amount of contamination. The minimum transmission value of a relatively large set of long detection lines is the detection line that has gone through the most amount of contamination. The ratio between these two transmission values is a good indicator of the global level of contamination on the panel

(39) Implementation

(40) FIG. 4a shows a surface 4 with global contamination 17.

(41) In step 310 of FIG. 3, a set of detection lines are selected for use in the contamination determination. In a preferred embodiment shown in FIG. 4b, detection lines from each emitter are used. For each of the emitters (x.sub.1, x.sub.2, x.sub.3 . . . ) along the short edge, a set (U.sub.x1, U.sub.x2, U.sub.x3 . . . ) of detection lines within 20 degrees of the horizontal axis of the panel is selected for use with the process. i.e. U.sub.x1 is a set of detection lines from emitter x.sub.1. For each of the emitters (y.sub.1, y.sub.2, y.sub.3 . . . ) along the long edge, a set (U.sub.y1, U.sub.y2, U.sub.y3 . . . ) of detection lines within 20 degrees of the vertical axis of the panel is selected for use with the process. i.e. U.sub.y1 is a set of detection lines from emitter y.sub.1.

(42) In step 320, the detection line with the lowest transmission values (i.e. weakest projection signal) from each of set (U.sub.x1, U.sub.x2, U.sub.x3 . . . ) is selected. The transmission values of the selected detection lines are summed.

(43) In step 330, the detection line with the highest transmission values (i.e. strongest projection signals) from each of set (U.sub.y1, U.sub.y2, U.sub.y3) is selected. The transmission values of the selected detection lines are summed.

(44) In step 340, a ratio of the sum of the highest transmission values and the sum of the lowest transmission values is output as a global contamination value by the system.

(45) $\mathrm{Global}\mathrm{Contamination}=\underset{i=1}{\overset{n}{.Math.}}\max \left(\mathrm{Uyi}\right)\text{:}\underset{i=1}{\overset{m}{.Math.}}\min \left(\mathrm{Uxj}\right)$

(46) As can be seen, both the first and second techniques described above are employed in this embodiment. However, each of these techniques may be employed alone or independently to determine the global contamination of the panel. In one embodiment using only the first technique, the average of set (U.sub.y1, U.sub.y2, U.sub.y3) is calculated and compared to the average of set (U.sub.x1, U.sub.x2, U.sub.x3 . . . ). The result is a ratio that increases with increasing contamination level of the panel.

(47) In an embodiment using only the second technique, either the average or maximum ratio within the subsets is used. This means that for each subset, the ratio between the strongest and weakest detection lines is calculated. All these ratios are averaged and used as a measure of the global contamination level. Alternatively, the highest ratio is determined and used as a measure of the global contamination level.

(48) In optional step 350, the global contamination is indicated on a display to a user with an instruction to clean the contaminated panel.

(49) Regional Contamination Determination

(50) FIG. 5 is a flow chart of a regional contamination detection process in an FTIR system. The process involves a sequence of steps 510-550 that are executed each time a determination of contamination on the panel is required which provides regional specific information about the location of the contamination.

(51) A measure of the regional contamination is most useful when the contamination is concentrated in a small area. An example of regional contamination may be a finger smudge, a water droplet, an object resting on the surface etc.

(52) The technique presented for regional contamination is similar to the second technique presented for global contamination determination. For a set of detection lines that have approximately the same transmission value when the panel is clean, the detection lines with the strongest and weakest transmission values respectively are determined. The ratio between the detection lines with the strongest and weakest transmission values increases as the contamination level on the panel increases. The line with the strongest transmission value from this subset will be the detection line that passes through the least amount of contamination and the detection line with the weakest transmission value will pass through the most amount of contamination.

(53) In the technique presented for regional contamination, the ratios for a plurality of subsets of the set of detection lines are determined. Preferably, subsets each comprise detection lines from a respective emitter, i.e. each subset has detection lines from one emitter.

(54) For each subset, the detection line most affected by contamination (i.e. the detection line with the minimum transmission value) is determined and used to determine a direction from the single emitter of the contamination affecting the detection line. This direction is determined from the known angle of the detection line from the single emitter. If the ratio determined from the subset is small, it is determined that no real indication of a regionalized contaminated area is made by the single emitter. If the ratio determined from the subset is high, probability is high of contamination in the direction indicated by the detection line with the weakest transmission value. By combining the contamination probability with the directional information from several different subsets, it becomes possible to determine a localized region on the panel that is contaminated, using techniques such as Filtered Back Projection, FFT-based algorithms, ART (Algebraic Reconstruction Technique), SART (Simultaneous Algebraic Reconstruction Technique), etc.

(55) Implementation

(56) FIG. 6a shows a surface 4 with regional or local contamination 27.

(57) In step 510 of FIG. 5, a set of detection lines are selected for use in the contamination determination. In a preferred embodiment shown in FIG. 6b, detection lines from each emitter are used. For each of the emitters (x.sub.1, x.sub.2, x.sub.3 . . . ) along the short edge, a set (U.sub.x1, U.sub.x2, U.sub.x3 . . . ) of detection lines within 20 degrees of the horizontal axis is selected for use with the process. For each of the emitters (y.sub.1, y.sub.2, y.sub.3 . . . ) along the long edge, a set (U.sub.y1, U.sub.y2, U.sub.y3) of detection lines within 20 degrees of the vertical axis is selected for use with the process. It is envisaged that different angular ranges are used to determine which detection lines are included in each set. A range of between 5 degrees and 45 degrees may provide useful results.

(58) In step 520, the detection lines with the highest and lowest transmission values from each of set U.sub.x1, U.sub.x2, U.sub.x3 are compared and a ratio (R.sub.x1, R.sub.x2, R.sub.x3 . . . ) between the highest and lowest transmission values is calculated for each set. Contaminated regions of the panel are likely to produce a greater variation in the transmission values of the set of detection lines traversing the contaminated region. This results in sets of detection lines with a higher ratio R value.

(59) FIG. 6c shows the surface 4 divided up into a grid in dependence on the horizontally and vertically facing emitters and corresponding detection line positions. In step 530, the ratio value R for each horizontal set (U.sub.x1, U.sub.x2, U.sub.x3, . . . ) and vertical set (U.sub.y1, U.sub.y2, U.sub.y3, . . . ) of detection lines are back projected (described below) to the grid locations covered by at least one detection line from the set. In a preferred embodiment, the weakest detection line from each set (i.e. the detection line from the set used to calculate R with the weakest transmission value) is used to determine how each grid location is affected by the ratio value R for each set.

(60) FIG. 6d shows the a map of surface 4 divided up into a grid comprising rectangular grid locations 30, each having centre point p.sub.i,j.

(61) Define p.sub.i,j=(x, y) to be the centre points of grid locations 30 of the map. Define .sub.l=(x, y) to be the positions of the emitters, d.sub.k=(x, y) to be the positions of the detectors. The normal to the detection line given by emitter l and detector k is defined as

(62) ${\stackrel{\_}{n}}_{\mathrm{kl}}=\frac{\mathrm{normal}\left({\stackrel{\_}{d}}_k-{\stackrel{\_}{e}}_l\right)}{||{\stackrel{\_}{d}}_k-{\stackrel{\_}{e}}_l{||}_2}=\frac{\left(-y,x\right)}{\sqrt{x^2+y^2}}.$

(63) In a preferred embodiment shown in FIG. 6e, the contribution to all centre points of grid locations in the map is computed for the weakest line 35 in each set, U. For each set, U, the minimum distance between the detection line, from emitter .sub.l to detector d.sub.k, and all grid points (by projection onto the normal vector n.sub.k,l) is computed:
s.sub.i,j=n.sub.k,l.Math.(p.sub.i,j.sub.l)

(64) For each set, U, the contribution to all grid points is computed according to
b.sub.i,j.sup.U=R.sub.U.Math.w(s.sub.i,j)

(65) Where R.sub.U is the ratio value calculated for the respective horizontal or vertical set and where the weight function, w, describes how much contribution a point gets depending on the distance from the detection line to the grid point. Some examples are

(66) $w\left(s\right)=e^{-s^2\text{/}2{}^2}$$w\left(s\right)=\{\begin{array}{cc}1& \mathrm{if}\left|s\right|<s_{\mathrm{threshold}}\\ 0& \mathrm{if}\left|s\right|s_{\mathrm{threshold}}\end{array}w\left(s\right)=\{\begin{array}{cc}\frac{s_{\mathrm{threshold}}-\left|s\right|}{s_{\mathrm{threshold}}}& \mathrm{if}\left|s\right|<s_{\mathrm{threshold}}\\ 0& \mathrm{if}\left|s\right|s_{\mathrm{threshold}}\end{array}$

(67) The contributions from all sets, U, are aggregated into a single map using the contributions from all sets

(68) $b_{i,j}=\underset{U}{.Math.}{b}_{i,j}^U$

(69) In another embodiment, the contribution to grid location b.sub.i,j.sup.U is computed according to the length of the detection line that passes that particular grid location.

(70) In a preferred embodiment, back projection of detection line is performed on two different maps comprising the grid shown in FIG. 6c. The first map is used to calculate back-projection values using the horizontal sets (U.sub.x1, U.sub.x2, U.sub.x3, . . . ) and the second map is used to calculate back-projection values using the vertical sets (U.sub.y1, U.sub.y2, U.sub.y3, . . . ). This results in two maps, b.sup.h (accumulated using horizontal sets) and by (accumulated using vertical sets).

(71) The last step combines the two maps using
b.sub.i,j=b.sub.i,j.sup.h.Math.b.sub.i,j.sup.v

(72) In an alternative embodiment, other combination functions may be envisaged, such as a summing of the maps.

(73) In step 540, the value of each grid location is compared with a threshold value to determine the presence of contamination. The grid coordinate (x.sub.2, y.sub.4) from FIG. 6c is determined to comprise contamination on the surface of the panel.

(74) In optional step 550 shown in FIG. 6f, the contaminated region is indicated on a display to a user with an instruction to clean the contaminated region of the panel.

(75) In an alternative embodiment of the invention, a triangulation technique is used to determine the location of contamination on the panel. First, the highest ratio from set (R.sub.x1, R.sub.x2, R.sub.x3 . . . ) is determined. Then, the direction of the weakest detection line corresponding to the highest ratio from set (R.sub.x1, R.sub.x2, R.sub.x3 . . . ) is determined. Similarly, the highest ratio from set (R.sub.y1, R.sub.y2, R.sub.y3 . . . ) is determined. Then, the direction of the weakest detection line corresponding to the highest ratio from set (R.sub.y1, R.sub.y2, R.sub.y3 . . . ) is determined. Triangulating the direction of the weakest detection line corresponding to the highest ratio from set (R.sub.x1, R.sub.x2, R.sub.x3 . . . ) with the direction of the weakest detection line corresponding to the highest ratio from set (R.sub.y1, R.sub.y2, R.sub.y3 . . . ) will provide an indication of the most contaminated region of the panel.

(76) Process Execution

(77) The contamination determination in FIGS. 3 and 5 may be executed separately from the data collection process in FIG. 2, e.g. on separate devices or on a single device (e.g. the signal processor 10 in FIG. 1). Alternatively, the processes in FIGS. 2, 3 and 5 may be integrated into one process for execution on a single device. FIG. 8 shows an example of a data processing device 10, which includes an input 810 for receiving the projection signals. The device 10 further includes a global contamination element (or means) 820 for performing steps 310-340, a regional contamination detection element (or means) 830 for performing steps 510-550, and an output element (or means) 840 for providing global and regional contamination determination values via an output 850.

(78) Hardware Device

(79) The device 10 may be implemented by special-purpose software (or firmware) run on one or more general-purpose or special-purpose computing devices. In this context, it is to be understood that each element or means of such a computing device refers to a conceptual equivalent of a method step; there is not always a one-to-one correspondence between elements/means and particular pieces of hardware or software routines. One piece of hardware sometimes comprises different means/elements. For example, a processing unit may serve as one element/means when executing one instruction, but serve as another element/means when executing another instruction. In addition, one element/means may be implemented by one instruction in some cases, but by a plurality of instructions in some other cases. Naturally, it is conceivable that one or more elements (means) are implemented entirely by analogue hardware components.

(80) The software controlled device 10 may include one or more processing units, e.g. a CPU (Central Processing Unit), a DSP (Digital Signal Processor), an ASIC (Application-Specific Integrated Circuit), discrete analogue and/or digital components, or some other programmable logical device, such as an FPGA (Field Programmable Gate Array). The device 10 may further include a system memory and a system bus that couples various system components including the system memory to the processing unit. The system bus may be any of several types of bus structures including a memory bus or memory controller, a peripheral bus, and a local bus using any of a variety of bus architectures. The system memory may include computer storage media in the form of volatile and/or non-volatile memory such as read only memory (ROM), random access memory (RAM) and flash memory. The special-purpose software and associated control parameter values may be stored in the system memory, or on other removable/non-removable volatile/nonvolatile computer storage media which is included in or accessible to the computing device, such as magnetic media, optical media, flash memory cards, digital tape, solid state RAM, solid state ROM, etc. The data processing device 10 may include one or more communication interfaces, such as a serial interface, a parallel interface, a USB interface, a wireless interface, a network adapter, etc, as well as one or more data acquisition devices, such as an A/D converter. The special-purpose software may be provided to the device 10 on any suitable computer-readable medium, including a record medium, and a read-only memory.

(81) Touch Display

(82) In one embodiment of the invention, the contamination detection function takes advantage of existing FTIR touch components such as those described in PCT publication WO2014042576 A3 Touch force estimation in an FTIR-based projection-type touch-sensing apparatus. Where the apparatus described in WO2014042576 is used to determine contact between an object and the panel, an embodiment of the present invention uses the same apparatus for determination of surface contamination of the panel.

(83) In a preferred embodiment, surface 4 is also a touch sensitive surface and processing element 10 is configured to determine, based on output signals of the light detectors 3, a light energy value for each light path; to generate a transmission value for each light path based on the light energy value; and to operate an image reconstruction algorithm on at least part of the thus-generated transmission values so as to determine the position of an object on the touch surface. The image reconstruction algorithm may be an algorithm for transmission tomography with a fan beam geometry.

(84) In one embodiment, the apparatus may be configured to be switchable between a touch detection mode and a contamination detection mode. In an alternative embodiment, the contamination detection runs in parallel to the touch detection and uses the same signals recorded for touch determination. In this embodiment, the contamination detection may be executed on separate processing hardware or on the same signal processing hardware provided for touch determination.

(85) In one embodiment, the contamination detection process runs at a lower frame rate than a touch detection process. Alternatively, the contamination detection process may be configured to collect and process only part of the contamination data in each frame. For example, contamination detection process is operated to use only emitters 1-5 from a first frame and collect the corresponding detector data, and then use only emitters 6-10 in the second frame etc. until all the emitters have been used. This method allows a reduction in the amount of processing used but leads to a slower update of the contamination mapping. However, compared with touch detection, detection of contamination is substantially less latency critical. Furthermore, there should be no changes in contamination during the time when the contamination detection process is used as it is preferably employed when there are no fingers present on the touch panel.

(86) Although embodiments of the invention may use the same recorded signal values to determine surface contamination as those recorded to determine touch, it is important to note that the techniques for determining touch as described by the prior art are fundamentally different to the techniques described herein for determining surface contamination.

(87) User Alerts

(88) In one embodiment of the invention, the contamination detection apparatus is overlaid on or integrated into a display device or monitor. This may be part of an FTIR type touch system (for example, a touch display) or just a contamination detection panel for a display, e.g. for applications requiring exceptional optical clarity. Contamination handling module 23 is configured to provide alerts to a user via an operating system call, a direct software interaction, or a hardware alert e.g. via an LED, separate display, or sound alert.

(89) FIGS. 7a-7c show embodiment of a software interface for providing contamination information to the user. In FIG. 7a, a determination of the global contamination is used to display a contamination value and corresponding contamination bar to a user. The contamination value and corresponding bar are used to indicate the general level of surface contamination on the screen and provides a prompt to the user to clean the screen. In one embodiment, the contamination value is updated as the user cleans the screen, providing the user with a real time update on the effectiveness of his cleaning efforts.

(90) In FIG. 7b, a determination of the regional contamination is used to display a region of the screen that is contaminated. In the embodiment shown, contaminated region of the screen is marked clean here as an indication to the user that the screen should be cleaned. In one embodiment, the size and position of a clean here box corresponds to the position and size of the contaminated region. In an alternative embodiment, the size or colour of the box may correspond to the degree of contamination in that region. In one embodiment, the contamination value is updated as the user cleans the screen, providing the user with a real time update on the effectiveness of his or her cleaning efforts, e.g. as the indicated portion of the screen is cleaned, the size of the box may shrink to indicate less contamination. Alternatively, the colour of the box fades from a first colour (e.g. red) to a second colour (e.g. green) as the screen becomes cleaner.

(91) In one embodiment, the clean here box is repositioned from a first area to a second area of contamination once a first area of contamination has been successfully cleaned.

(92) In an embodiment shown in FIG. 7c, a regional contamination indicator is combined with the global contamination indicator. This provides the user with an indicator of which section of the panel to focus his or her cleaning efforts, as well as an indicator of their overall progress towards a completely clean screen.

(93) In other embodiments of the invention, the software interface is configured to provide the user with an indication of success once either the regional contamination or the global contamination has been successfully cleaned.

(94) In another embodiment of the invention, the user interface is configured to provide an indication of the estimated loss of clarity in contaminated regions of the panel. The estimated loss of clarity may be calculated as a function of the determined regional or global contamination.

(95) In another embodiment of the invention, the user interface is configured to provide a warning once either global or regional contamination passes a threshold. The warning may indicate the possibility and/or degree of degradation in touch performance of a touch sensitive panel. In an alternative embodiment, the warning may indicate to the user the risk of spread of infection from fluids deposited on the panel.

(96) In another embodiment of the invention, the user interface is configured to provide an indication of the environment humidity and/or condensation affecting the panel in dependence on the global and/or regional contamination determinations.

(97) Non-Touch Panel

(98) In other embodiment, the contamination detection is used to determine whether contamination is present on optically critical applications, including solar panels, windows, museum displays, eye wear, and lenses of all types.

(99) In one embodiment, contamination 7 maybe detected on both the top surface 4 and bottom surface 5 simultaneously.

(100) While the invention has been described in connection with what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not to be limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications and equivalent arrangements included within the spirit and the scope of the appended claims.