Lecture topics: - Introduction, computer image processing, basic optics, aperture, depth of field, lens brightness, basic calculations. - CCD and CMOS sensors, conversion of photons to electrical charge, exposure time, electronic shutter, AES, AGC functions. - Lens, method of attachment, choice of lens, intermediate rings, sensor sizes, special lenses, colour and polarizing filters, illuminators. Chromatic and geometric lens errors. - Illumination, spectrum, fluorescent lamps and LEDs, use of DLP, special lighting. - TV standard, analogue signal and its transmission, pixel and image geometry, HDMI, DisplayPort. - Image signal sampling, AD converters, colour spaces, digital interfaces: Camera-Link, DVP, LVDS. - Acquiring quality image. Conversion table, histogram equalization, contrast enhancement, noise suppression, intensity transformation. - Image pre-processing, sharpening, edge detection, 2D convolution. - Discrete linear integral transforms - 2D DFT(FFT), DCT, wavelet transform, use of LDT in image (pre-)processing, lossy and lossless image compression. - Software tools for working with digital image data, OpenCV. - Industrial interfaces for PC, USB3.0, GigE, Camera-Link, GenICAM, modular systems, suitability of use. - Special sensors, colour sensors, Bayer mask, Foveon, infrared sensors, multi and hyperspectral sensors and cameras, depth sensing, distance sensing, stereoscopy. - Use of specialised image processing tools: DSP, GPU, FPGA, AXI standard, DMA. - Compact industrial systems for building computer vision applications, use of ANN - CNN, RNN in image processing. Labs content: - Basic calculations in optics. - Introduction to the development environment. - Measurement of optical properties of lenses, correction of lens defects. - Histogram equalization, 2D convolution, custom project. - Colour space conversion, transformations. - Image quality metrics, lossy and lossless image compression. - Distance and depth measurements. - Image processing library tools - OpenCV, Matlab. - Semester thesis. - Field trips.
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In this course, students will learn the basics of image capture and processing and with the hardware necessary for integration into computer image processing systems. The lectures will provide a comprehensive overview of the design of such a system, from the illuminator, to the optical system, to the selection of an appropriate camera, evaluation hardware, and the construction of an image analysis program. In the tutorials, students will be able to verify the lecture material practically with different programming tools and different HW devices (Industrial cameras, lenses and illuminators, specialized IR cameras, kinect/hololens, 3D scanners, etc.). In practice, the student should then be able to independently design and apply such a system.
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