Introduction to image processing: Image processing applications, image processing goals, image function, image representation, sampling and quantization, gray scale, binary (black and white), and color images, histograms, noise in images. Color image models: RGB, HIS, YIQ models. Image enhancement, convolution and filtering: Point processing, histogram equalization, histogram modeling, and histogram specification, spatial filtering – image smoothing, median filtering Edge detections: Sobel, Prewit, Laplacian and Canny edge detectors Image segmentation: Thresholding Shape detection, image matching and texture: image moments, central moments, moment invariants, template matching, area correlation, texture description, Image morphology: Basic morphological concepts, structuring elements, erosion, dilation, thinning, thickening, opening, and closing operations.
