Abstract:
A surface measurement device includes a rotating platform, a motion lever, a measuring module and a control module. The rotating platform rotates an object at a rotating speed. The motion lever is above the rotating platform. The measuring module moves to a variety of measuring positions on the motion lever. When the measuring module is at one of the measuring positions, the measuring module measures the heights of a plurality of sampling points on the surface of the object in a sampling frequency. The control module selectively modifies the rotating speed of the rotating platform or the sampling frequency of the measuring module according to the measuring position of the measuring module to make the distance between the sampling points in at least a region of the surface of the object match a sampling rule.
Abstract:
A three-dimension measurement device includes a moving device, a projecting device, a surface-type image-capturing device and a processing device. The moving device carries an object, and moves the object to a plurality of positions. The projecting device generates a first light to the object. The surface-type image-capturing device senses a second light generated by the object in response to the first light to generate a phase image on each of the positions. The processing device is coupled to the surface-type image-capturing device and receives the phase images. The processing device performs a region-of-interest (ROI) operation for the phase images to generate a plurality of ROI images. The processing device performs a multi-step phase-shifting operation for the ROI images to calculate the surface height distribution of the object.
Abstract:
A temperature sensing apparatus configured to measure a temperature distribution of a surface to be measured is provided. The temperature sensing apparatus includes a lens set, a filtering module, a plurality of sensor arrays, and a processing unit. The lens set is configured to receive radiation from the surface to be measured. The filtering module is configured to filter the radiation from the lens set into a plurality of radiation portions respectively having different wavelengths. The sensor arrays are configured to respectively sense the radiation portions. The processing unit is configured to calculate an intensity ratio distribution of the radiation between the different wavelengths according to the radiation portions respectively sensed by the sensor arrays and determine the temperature distribution according to the intensity ratio distribution. A laser processing system and a temperature measuring method are also provided.
Abstract:
An optical measurement system comprises a polarization beam splitter for dividing an incident beam into a reference beam and a measurement beam, a first beam splitter for reflecting the measurement beam to form a first reflected measurement beam, a spatial light modulator for modulating the first reflected measurement beam to form a modulated measurement beam, a condenser lens for focusing the modulated measurement beam to an object to form a penetrating measurement beam, an objective lens for converting the penetrating measurement beam into a parallel measurement beam, a mirror for reflecting the parallel measurement beam to form an object beam, a second beam splitter for reflecting the reference beam to a path coincident with that of the object beam, and a camera for receiving an interference signal generated by the reference beam and the object beam to generate an image of the object.
Abstract:
A structured light generating device and a measuring system and method are provided. The structured light generating device includes: a light modulating element for receiving a projection light beam and modulating the projection light beam into a first structured light beam having a pattern, and a light shifting element corresponding to the light modulating element for receiving and shifting the first structured light beam to generate a second structured light beam having the pattern. A shift difference is formed between the first structured light beam and the second structured light beam, and the first structured light beam and the second structured light beam are superimposed to form a superimposed structured light beam so as to improve resolution.
Abstract:
A measurement system is configured to measure a surface structure of a sample. The surface of the sample has a thin film and a via, the depth of the via is larger than the thickness of the thin film. The measurement system includes a light source, a first light splitter, a first aperture stop, a lens assembly, a second aperture stop, a spectrum analyzer and an analysis module. The first light splitter disposed in the light emitting direction of the light source. The first aperture stop disposed between the light source and the first light splitter. The lens assembly is disposed between the first light splitter and the sample. The second aperture stop is disposed between the lens assembly and the first light splitter. The spectrum analyzer is disposed to at a side of the first light splitter opposite to the sample.
Abstract:
A structured light generating device and a measuring system and method are provided. The structured light generating device includes: a light modulating element for receiving a projection light beam and modulating the projection light beam into a first structured light beam having a pattern, and a light shifting element corresponding to the light modulating element for receiving and shifting the first structured light beam to generate a second structured light beam having the pattern. A shift difference is formed between the first structured light beam and the second structured light beam, and the first structured light beam and the second structured light beam are superimposed to form a superimposed structured light beam so as to improve resolution.
Abstract:
A method of training AI for label-free cell viability determination includes a step of providing a cell sample, a step of obtaining a fluorescence image and a DHM image of the cell sample, a step of determining a first cell viability of the cell sample according to the fluorescence image of the cell sample, a step of labeling the DHM image of the cell sample as a model specifying the first cell viability, and a step of performing AI training by using the model containing the DHM image of the cell sample.
Abstract:
A close-loop deep brain stimulation algorithm system for Parkinson's disease includes a memory and a processor. The processor includes a deep brain stimulation (DBS) simulation module, a virtual brain network module, a feature extraction module, and a reinforcement learning module. The deep brain stimulation simulation module is adapted to combine a deep brain stimulation waveform according to the stimulation frequency and the stimulation amplitude and output the deep brain stimulation waveform. The virtual brain network module is adapted to receive the deep brain stimulation waveform to output a synaptic signal and calculate a reward parameter. The feature extraction module is adapted to receive the synaptic signal and extract a plurality of feature values according to the synaptic signal. The reinforcement learning module is adapted to train a deep brain stimulation neural network based on the feature values and reward parameter and output the stimulation frequency and the stimulation amplitude to the deep brain stimulation simulation module.
Abstract:
A detection system for a multilayer film is provided. The detection system for a multilayer film includes a light source device, a first image capture device, a second image capture device and an image processing device. The light source device projects a pair of parallel incident light to a transparent multilayer film obliquely. The pair of parallel incident light is projected onto the transparent multilayer film for producing and enabling a forward scattered light and a back scattered light to be projected therefrom. The first image capture device captures the back scattered light to produce a first image. The second image capture device captures the forward scattered light to produce a second image. The image processing device is coupled to the first image capture device and the second image capture device. The image processing device is used to compares and detect the differences between the second image and the first image.