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The Image Processing and Measurement Cookbook by Dr. Basic image processing demos showing some basic image processing filters: thresholding, Gaussian filter, and Canny edge detector using MATLAB. The SUSAN algorithms cover image noise filtering, edge finding and corner finding. Image Authentication for a Slippery New Age, Dr. Also see Recognition, Faces and Recognition, Fingerprints below. Jean Vezina’s automatic tree species identification from digitized aerial photographs.
Data Structures: Your Mind Doesn’t Process Pixels, so why Should Your Software? Gives example of Kanizsa Square that has illusory edges. Canny, “A computational approach to edge detection”, IEEE Patt. Chapter 12, Edges and Lines, pp. Vision Systems Design, July 1998, pp. Digital Image Processing: Principles and Applications, pp. Vision Systems Design, June 1998, pp.
4, Enhancement in the Frequency Domain, pp. Note from Lazikas o Pontios about convolution filters. RGB channels in an image is usually wrong. 3, Linear filtering using convolution, High Performance Computer Imaging. Diagram of optimal way to compute median value from 3×3 array in hardware.
Use the same logic in software. Median filters are useful tools in digital signal processing. Wesley examines their use for removing impulsive signal noise while maintaining signal trends. Tim presents an algorithm that implements this concept. Chapter 7, Processing Binary Images, pp. Vision Systems Design, March 1997, pp. SDC Morphology Toolbox for MATLAB: includes fast queue-based algorithms for distance transform, watershed, reconstruction, labeling, area-opening, etc.
2, Removal of Blur Caused by Uniform Linear Motion, pp. Chapter 9, Recognition and Interpretation, pp. Scalar Quantization Specification for compression of digitized gray-scale fingerprint images. Chapter 8, Optical Character Recognition, pp. Understanding Pattern Recognition, Visions Systems Design, July 1999. Understanding More Pattern-Recognition Techniques, Visions Systems Design, Aug 1999, pp.
Optimizing Vision Applications: Which is Better, Blob-Centroid or Grayscale Search? Chapter 8, Representation and Description, pp. Practical Handbook on Image Processing for Scientific Applications p. Note from Lazikas o Pontios abut Resampling to zoom.
Researchers are using blind-image deconvolution to automatically deblur telescope and microscope images. Chapter 3, Correcting Image Defects, pp. Chapter 9, Restoration and Reconstruction, pp. High Accuracy Rotation of Images,” in Computer Vision, Graphics and Image Processing, Vol.
One-pass and multipass rotation, Section 8. In Windows NT the plgblt API call can be used for bitmap rotation if the RC_BITBLT is supported by a device. Many image-analysis tasks must first separate the image into clearly defined regions. Lee’s algorithm performs such a separation and presents the results in a fashion amenable to further study. Chapter 6, Segmentation and Thresholding, pp.
Active contours — or snakes — are computer-generated curves that move within images to find object boundaries. USGS Imaging spectroscopy analysis: identify and map materials through spectroscopic remote sensing, on the earth and throughout the solar system. Stereoscopic, or true 3-D, images take into account depth information that’s lost when conventional 3-D images are projected onto a PC’s 2-D screen. In addition to discussing hardware and software stereoscopic requirements, our authors present and implement algorithms for generating left- and right-eye views fundamental to stereoscopic viewing. Chapter 14, Scale and Texture, pp. Affine texture mapping is fundamental to many forms of 3D rendering, including light interpolation and other sampling type operations. 8, High Performance Computer Imaging, Special-effects filters.
Chatterji, “An FFT-Based Technique for Translation, Rotation, and Scale-Invariant Image Registration,” IEEE Trans. Abstract from ACM Computing Surveys, Vol 24. An overview of medical image registration methods. Fast Hartley Transform is covered under U.