In one embodiment, a light sensor, such as a camera, records an image through the surface with the residue to produce a stained image. A processor associated with the camera identifies object outlines within the image using a machine learning model, and smooth the colors within the object outlines. In another embodiment, the light sensor is placed beneath a dual-mode region of a display containing the residue. The dual-mode region can be opaque and function as part of the display, or can be transparent and allow environment light to reach the light sensor. Initially, the processor determines the position of the residue by causing the dual-mode region to display a predetermined pattern, while the light sensor records the predetermined pattern. Using the determined position of the residue, the processor corrects the pixels within the residue in the recorded image, by interpolating the values of the pixels outside of the residue.

A portable fluorescence detection system for a test unit comprises a housing, a light source module and a image capturing module. The housing has a receiving area for accommodating the test unit. The light source module is disposed in the housing and projecting light towards the receiving area. The image capturing module is disposed in the housing and receiving fluorescence light from the receiving area so as to capture an image. The above-mentioned system can be applied to the point-of-care testing.

Fuel sampling systems are disclosed. In one embodiment, a fuel sampling system includes an optical capture device and an analysis computing device that stores logic for implementing an evaluation sequence. During the evaluation sequence, the analysis computing device performs at least the following: receive a captured image from the optical capture device, identify areas of highest contrast in the captured image, and determine if the areas of highest contrast define a ring. If the areas of highest contrast define a ring, evaluate a contrast ratio between the ring and areas outside of the ring, and determine if the captured image reflects a fuel sample that exceeds a predetermined limit of propensity for settling. If so, indicate that the captured image reflects a fuel sample that is not acceptable. Otherwise, indicate that the captured image reflects a fuel sample that is acceptable.

In one embodiment, a light sensor, such as a camera, records an image through the surface with the residue to produce a stained image. A processor associated with the camera identifies object outlines within the image using a machine learning model, and smooth the colors within the object outlines. In another embodiment, the light sensor is placed beneath a dual-mode region of a display containing the residue. The dual-mode region can be opaque and function as part of the display, or can be transparent and allow environment light to reach the light sensor. Initially, the processor determines the position of the residue by causing the dual-mode region to display a predetermined pattern, while the light sensor records the predetermined pattern. Using the determined position of the residue, the processor corrects the pixels within the residue in the recorded image, by interpolating the values of the pixels outside of the residue.

A method for three-dimensional measuring of objects with triangulation includes projecting light structures onto an object, capturing the light structures with optoelectronic image capture, and computer-assisted evaluation of the captured images for measuring the object. The light structures are projected in a first wavelength range and the image capture detects the wavelength range that has the intensities caused by fluorescence of the object. The wavelengths emitted from the object are filtered when the projected light structures are captured. Both the wavelength range used for projecting light structures and the wavelength range having the fluorescence are detected for the same image capture and the transmission of the wavelength range having the fluorescence is larger than the transmission of the wavelength range used for projecting light structures. Electronic or electromechanical components and components made of plastics material are measured as the objects which have a self-fluorescent surface.

The present invention discloses improved analytical methods that use spectral quality, classification, and quantitative algorithms to properly vet date and thereby enable the use of conventional spectroscopic methods to easily, quickly, and automatically identify and quantify chemical species in samples.

Disclosed herein are systems, methods, and devices for determining a presence or concentration of a chemical in a sample based on image analysis. In one embodiment, a computing system for image analysis includes one or more hardware computer processors configured to execute software instructions and one or more storage devices storing software instructions for execution by the one or more hardware computer processors configured to cause the computing system to perform the following steps. The computing system receives imaging data of at least one sample droplet of a sample and at least one reagent. One or more imaging properties are identified from the imaging data and a result is generated. The result indicates the presence or concentration of a chemical in the sample based on the identified imaging properties. The computing system stores the imaging data and the result.

A portable fluorescence detection system for a test unit comprises a housing, a light source module and a image capturing module. The housing has a receiving area for accommodating the test unit. The light source module is disposed in the housing and projecting light towards the receiving area. The image capturing module is disposed in the housing and receiving fluorescence light from the receiving area so as to capture an image. The above-mentioned system can be applied to the point-of-care testing.

A portable fluorescence analysis system comprises a fluorescence strip, a fluorescence excitation device and a mobile Internet device. The fluorescence strip comprises a fluorescence probe configured for detecting an analyte within a specimen. The fluorescence excitation device comprises a sleeve and an excitation light source module. The fluorescence strip is arranged at the one open end of the sleeve. The excitation light source module is arranged at the same opening side of the sleeve and configured for providing an excitation light to excite the fluorescence probe to generate fluorescence. The mobile Internet device comprises an image capturing module and configured for capturing a fluorescence image of the fluorescence strip via the other opening of the sleeve and analyzing fluorescence intensity of the fluorescence image to determine the content of the analyte. The above-mentioned system can be applied to the point of care testing.

A measurement instrument comprises a cylindrical cell that stores a measurement fluid, a light source that is arranged outside the cell and irradiates the measurement fluid with inspection light, a detector that is arranged outside the cell and detects transmitted light or scattered light generated from the measurement fluid, a cleaning mechanism that is arranged inside the cell and cleans an inner peripheral surface of the cell, and a drive mechanism that rotates the cell about a central axis.