Thermal image sensing system and thermal image sensing method
11290663 · 2022-03-29
Assignee
Inventors
- Han-Kuei Fu (New Taipei, TW)
- Hsueh-Chih Chang (Changhua County, TW)
- Shih-Yi Wen (Hsinchu, TW)
- Hung-Lieh Hu (Hsinchu, TW)
Cpc classification
H04N23/11
ELECTRICITY
G01J5/20
PHYSICS
International classification
G01J5/20
PHYSICS
Abstract
A thermal image sensing system including at least one thermal sensor, at least one light sensor, an image identification module, a storage module and a computing module is provided. The thermal sensor senses thermal radiation emitted by an object and generates a thermal radiation image signal correspondingly. The light sensor senses visible light reflected by the object and generates at least one visible light image signal correspondingly. The image identification module receives the visible light image signal generated by the light sensor and determines a material of the object according to the at least one visible light image signal. The storage module stores a radiation coefficient of the material of the object. The computing module calculates a surface temperature of the object according to the radiation coefficient of the material of the object and the thermal radiation emitted by the object. A thermal image sensing method is also provided.
Claims
1. A thermal image sensing method, comprising: sensing thermal radiation emitted by an object and generating a thermal radiation image signal correspondingly; sensing a visible light reflected by the object and generating at least one visible light image signal correspondingly; determining a material of the object according to the at least one visible light image signal; determining a radiation coefficient of the material of the object according to the material of the object; and calculating a surface temperature of the object according to the radiation coefficient of the material of the object and the thermal radiation emitted by the object, wherein the step of sensing the visible light reflected by the object and generating the at least one visible light image signal correspondingly comprises: filtering s-polarized light in the visible light reflected by the object; and sensing p-polarized light in the visible light reflected by the object and generating a first light signal, and wherein the step of determining the material of the object according to the at least one visible light image signal comprises: determining the material of the object according to the first light signal.
2. The thermal age sensing method according to claim 1, wherein the step of sensing the visible light reflected by the object and generating the at least one visible light image signal correspondingly further comprises: sensing the p-polarized light and the s-polarized light in the visible light reflected by the object and generating a second light signal, wherein the material of the object is determined according to both of the first light signal and the second light signal.
3. A thermal image sensing method, comprising: sensing thermal radiation emitted by an object and generating a thermal radiation image signal correspondingly; sensing a visible light reflected by the object and generating at least one visible light image signal correspondingly; determining a material of the object according to the at least one visible light image signal; determining a radiation coefficient of the material of the object according to the material of the object; and calculating a surface temperature of the object according to the radiation coefficient of the material of the object and the thermal radiation emitted by the object, wherein the step of sensing the visible light reflected by the object and generating the at least one visible light image signal correspondingly comprises: separating s-polarized light from p-polarized light in the visible light reflected by the object; sensing the p-polarized light in the visible light reflected by the object and generating a first light signal; and sensing the s-polarized light in the visible light reflected by the object and generating a third light signal, wherein the step of determining the material of the object according to the at least one visible light image signal comprises: determining the material of the object according to the first light signal and the third light signal.
Description
BRIEF DESCRIPTION OF THE DRAWINGS
(1) The accompanying drawings are included to provide a further understanding of the disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate embodiments of the disclosure and, together with the description, serve to explain the principles of the invention.
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DETAILED DESCRIPTION OF DISCLOSED EMBODIMENTS
(9) The directional terms mentioned in the implementations, for example, “above”, “below”, “front”, “back”, “left”, and “right”, refer to the directions in the accompanying drawings. Therefore, the directional terms are only used for description instead of limiting the disclosure.
(10) In the accompanying drawings, the drawings illustrate general features of methods, structures, and/or materials used in the particular exemplary embodiments. However, the drawings should not to be interpreted as defining or limiting the scope or nature of the exemplary embodiments. For example, relative sizes, thicknesses and positions of film layers, regions, and/or structures may be reduced or enlarged for clarity.
(11) In the implementations, same or similar reference numerals are used to indicate same or similar components, and details may be omitted. In addition, features in different exemplary embodiments may be combined with each other as long as no conflict occurs, and simple equivalent changes and modifications made in accordance with the specification or the claims still fall within the scope of this patent.
(12) Terms such as “first” and “second” used in the specification or the claims are used to name discrete components or to distinguish between different embodiments or ranges, and are not intended to define the upper or lower limit of the number of components or the manufacturing order or setting order of components. Furthermore, one component/film layer being disposed on (or above) another component/film layer may include two cases, that is, there are additional components/film layers between the two components/film layers or there are no additional components/film layers between the two components/film layers. In other words, the component/film layer may be disposed directly or indirectly on (or above) the another component/film layer. On the other hand, the component/film layer being disposed directly on (or above) the another component/film layer indicates that the two components/film layers are in contact with each other and there are no additional components/film layers between the two components/film layers.
(13) In this text, a thermal image sensing system is suitable for acquiring a thermal image of an object (which may also be referred to as an object to be tested). The thermal image represents an image of thermal radiation emitted by a surface of the object. According to the blackbody radiation law, all objects with temperatures above absolute zero may emit a thermal radiation (such as infrared radiation), and energy radiated by the object increases with the increase of the temperatures. Therefore, a surface temperature of the object may be known according to the thermal image of the object.
(14) According to the Stefan-Boltzmann law, as shown in Formula 1, the total energy E radiated per unit time by a unit area of the surface of one object is a function of an absolute temperature T and a radiation coefficient ε (a radiation coefficient of a blackbody), and σ is a Stefan-Boltzmann constant.
E=εσT.sup.4 Formula 1
(15) Table I illustratively lists radiation coefficients of a variety of common non-metal substances and metal substances. According to Table I, most of the non-metal substances have a radiation coefficient more than 0.9, while most of the metal substances have a radiation coefficient less than 0.3. Therefore, in the thermal image shot by the thermal image sensing system, if the radiation coefficient of the object (especially a metal substance) is not corrected, the surface temperature of the metal substance will be underestimated a lot.
(16) TABLE-US-00001 TABLE I Non-metal Radiation Metal Radiation substance coefficient substance coefficient Asbestos 0.95 Aluminium 0.02 to 0.1 (not oxidized) Ceramic 0.95 Aluminium 0.02 to 0.4 (oxidized) Cloth 0.95 Lead (polished) 0.05 to 0.1 Glass (flat) 0.85 Lead (coarse) 0.4 Paint (alcohol-free) 0.9 to 0.95 Lead (oxidized) 0.2 to 0.6 Paper (any color) 0.95 Brass (polished) 0.01 to 0.05 Plastic (light-proof) 0.95 Brass (oxidized) 0.5 Rubber 0.95 Zinc (polished) 0.03 Wood (natural) 0.9 to 0.95 Zinc (oxidized) 0.1
(17) In order to improve the problem that the surface temperature of the metal substance is underestimated, embodiments of the disclosure provide a thermal image sensing system and a thermal image sensing method, which can calculate the surface temperature of the metal substance by correcting the radiation coefficient of the metal substance. The detailed method is explained later.
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(19) The at least one thermal sensor (such as the thermal sensor 10) is suitable for sensing thermal radiation R emitted by an object OBJ. For example, the thermal sensor 10 may be an infrared light sensor, and is suitable for sensing infrared light from the object OBJ and generating a thermal radiation image signal RS correspondingly, but the type of the thermal sensor 10 is not limited thereto.
(20) The at least one light sensor (such as the light sensor 11) is suitable for sensing visible light L reflected by the object OBJ, receiving the visible light L, and generating at least one visible light image signal SS correspondingly. For example, the light sensor 11 may be a photodiode, a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS) element, but it is not limited to thereto.
(21) In the present embodiment, as shown in
(22) In the present embodiment, as shown in
(23) The image identification module 12 is suitable for receiving the at least one visible light image signal SS generated by the at least one light sensor (such as the light sensor 11) and determining a material of the object OBJ according to the at least one visible light image signal SS. For example, the image identification module 12 may analyze parameters such as a surface appearance and/or a color of the object OBJ by using artificial intelligence (AI) or an algorithm, so as to determine the material of the object OBJ.
(24) The image identification module 12 may be implemented as a software module, a firmware module, or a hardware circuit. For example, the image identification module 12 may include at least one graphics processing unit (GPU) or similar processing chip to perform machine vision-based image identification. Alternatively, in one embodiment, the image identification module 12 is a program code that may be loaded into the storage module 13 and executed by the computing module 14 or a processor. In addition, the image identification module 12 may have an AI structure such as machine learning and may continuously improve the image identification performance through training.
(25) The storage module 13 stores a radiation coefficient of the material of the object OBJ, but is not limited thereto. In one embodiment, the storage module 13 may store the radiation coefficients of various materials/substances and other desired information. For example, the storage module 13 may be a volatile storage medium or a non-volatile storage medium in an electronic device. The volatile storage medium may be a random access memory (RAM), and the non-volatile storage medium may be a read only memory (ROM), a solid state hard disk (SSD), or a hard disk (HDD). In one embodiment, the storage module 13 may also be a database stored in a cloud.
(26) The computing module 14 calculates a surface temperature of the object OBJ according to the radiation coefficient of the material of the object OBJ and the thermal radiation R emitted by the object OBJ. For example, the computing module 14 may include a central processing unit (CPU) or other programmable general-purpose or special-purpose microprocessors, digital signal processors (DSPs), programmable controllers, application specific integrated circuits (ASICs), programmable logic devices (PLDs), or other similar devices or a combination of these devices.
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(28) In step 200, a thermal sensor may be used to sense the thermal radiation emitted by the object, so as to acquire a thermal image of the object. In step 202, a light sensor may be used to sense the visible light reflected by the object, so as to acquire a visible light image of the object. In step 204, an image identification module may determine the material of the object according to the visible light image. For example, analysis may be performed according to parameters such as a surface appearance and/or a color of the object in the visible light image. For example, the material of the object may be determined according to the metal luster of the object in the visible light image, but it is not limited thereto. In step 206, the image identification module may search radiation coefficient information stored in a storage module for the radiation coefficient of the material of the object. In step 208, a computing module may calculate (such as substituting Formula 1) the surface temperature of the object according to the found radiation coefficient and the thermal radiation emitted by the object, and optimize/correct the thermal image acquired in step 200 accordingly.
(29) For example, feature matching (such as matching of positions and object sizes) may be performed through the thermal image acquired by the thermal sensor and the visible light image acquired by the light sensor, and the image identification module is used to identify the object in the visible light image, determine the material of the object, and find the radiation coefficient of the material of the object. Then, a temperature of a region where a metal substance is located in the thermal image of step 200 is optimized by the computing module, so that the surface temperature of the object displayed by the optimized thermal image conforms to an actual surface temperature of the object. In this way, compared to obtaining of the thermal image of the object only by the thermal sensor, the obtaining of the thermal image of the object by the cooperation of the thermal sensor and the light sensor can effectively avoid underestimation of the surface temperature of the metal substance, and the surface temperature of the object display by the thermal image is relatively consistent with the actual surface temperature of the object.
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(31) The polarizer 15 is suitable for filtering light having a specific polarization direction in visible light L. For example, s-polarized light has a relatively high reflectivity on a metal surface, which tends to generate a white picture (a highly reflective region) in the visible light image. If the white picture shields the image of the object, the difficulty of material identification will be increased, or the accuracy of the material identification will be reduced. Therefore, the polarizer 15 may be a polarizer that filters the s-polarized light LS in the visible light L and allows p-polarized light LP in the visible light L to pass. The polarizer 15 is used to filter the s-polarized light LS in the visible light L and allow the p-polarized light LP in the visible light L to pass, which contributes to eliminate the highly reflective region, thereby obtaining a relatively clear/complete image (a visible light image) of the object and improving the accuracy of the material identification.
(32) Under the structure provided with the polarizer 15, in step 202 of
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(35) Referring to
(36) Under the structure provided with the polarizer 15A or the polarizer 15B, the material identification is performed by the visible light image captured by the single light sensor (such as the light sensor 11 of
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(38) In the present embodiment, the polarizer 15 is suitable for allowing the p-polarized light to pass and filtering the s-polarized light. In step 202 of
(39) Referring to
(40) In the present embodiment, the light splitting element 17 is suitable for reflecting the infrared light (the thermal radiation R) and allowing the visible light L to penetrate, and the polarizer 15 is disposed between the light splitting element 17 and the light sensor 11. However, in another embodiment, the polarizer 15 may also be disposed in the light sensor 11. In addition, the light splitting element 17 may also reflect the visible light L and allow the infrared light (the thermal radiation R) to penetrate. Correspondingly, the positions of the thermal sensor 10 and the light sensor 11 are interchanged, and the polarizer 15 is disposed between the light splitting element 17 and the light sensor 11 or disposed in the light sensor 11.
(41) The thermal image sensing system 1C may include other elements according to different requirements. For example, the thermal image sensing system 1C may further include a condensing element 18. The condensing element 18 may provide an effect of converging light, and is suitable for allowing the infrared light (the thermal radiation R) and visible light L to pass. For example, the condensing element 18 may include at least one lens.
(42) In
(43) Referring to
(44) The material identification may also be performed by using two light sensors to capture images of different polarized light. Under the structure of
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(46) Based on the above, the thermal image sensing system and the thermal image sensing method of the disclosure may use the visible light image to determine the material of the object, and thus correct the surface temperature of the metal substance, so that the corrected/optimized surface temperature of the object displayed by the thermal image conforms to the actual surface temperature of the object. In one embodiment, the highly reflective region may be eliminated by the arrangement of the at least one polarizer, and the relatively clear/complete image of the object (the visible light image) may be obtained, thereby improving the accuracy of the material identification. In one embodiment, the combined design of various polarizers may assist in determining the material of the metal substance. In one embodiment, the arrangement of the plurality of light sensors and the single polarizer may assist in determining the material of the metal substance. In one embodiment, the thermal image sensing system may include the sensing module formed by arraying the plurality of thermal sensors and the plurality of light sensors.
(47) Although the disclosure is described with reference to the above embodiments, the embodiments are not intended to limit the disclosure. A person of ordinary skill in the art may make variations and modifications without departing from the spirit and scope of the disclosure. Therefore, the protection scope of the disclosure should be subject to the appended claims.