PGA Based Thresholding Schemes for Image Segmentation

In this book, the problem of image segmentation has been addressed using the notion of thresholding. Since the focus of this work is primarily on object/objects background classi¿cation and fault detection in a given scene, the segmentation problem is viewed as a classi¿cation problem. In this regard, the notion of thresholding has been used to classify the range of gray values and hence classi¿es the image. The gray level distributions of the original image or the proposed feature image have been used to obtain the optimal threshold. A Minimum Mean Square Error (MMSE) based FL and FB schemes have been proposed to deal with fault detection in a given scene whose histogram does not exhibit clear bimodality and almost becomes unimodal. Adaptive thresholding based schemes have been proposed to separate object and background in images with nonuniform lighting conditions.