Emerging Trends in Image Processing, Computer Vision, and Pattern Recognition, 1st Edition (2015)
Part I. Image and Signal Processing
Chapter 1. Denoising camera data
Chapter 2. An approach to classifying four-part music in multidimensional space
Chapter 3. Measuring rainbow trout by using simple statistics
Chapter 4. Fringe noise removal of retinal fundus images using trimming regions
Chapter 6. Rebuilding IVUS images from raw data of the RF signal exported by IVUS equipment
Chapter 13. Automatic mass segmentation method in mammograms based on improved VFC snake model
Chapter 14. Correction of intensity nonuniformity in breast MR images
Chapter 15. Traffic control by digital imaging cameras
Chapter 16. Night color image enhancement via statistical law and retinex
Part II. Computer Vision and Recognition Systems
Chapter 17. Trajectory evaluation and behavioral scoring using JAABA in a noisy system
Chapter 19. A rough fuzzy neural network approach for robust face detection and tracking
Chapter 20. A content-based image retrieval approach based on document queries
Chapter 21. Optical flow-based representation for video action detection
Chapter 22. Anecdotes extraction from webpage context as image annotation
Chapter 23. Automatic estimation of a resected liver region using a tumor domination ratio
Chapter 25. Biometric analysis for finger vein data
Chapter 26. A local feature-based facial expression recognition system from depth video
Chapter 27. Automatic classification of protein crystal images
Chapter 29. Effective finger vein-based authentication
Part III. Registration, Matching, and Pattern Recognition
Chapter 32. Surface registration by markers guided nonrigid iterative closest points algorithm
Chapter 33. An affine shape constraint for geometric active contours
Chapter 34. A topological approach for detection of chessboard patterns for camera calibration
Chapter 36. Distances and kernels based on cumulative distribution functions
Chapter 37. Practical issues for binary code pattern unwrapping in fringe projection method
Chapter 38. Detection and matching of object using proposed signature