Image Segmentation plays vital role in Computer Vision and Digital Image Processing. It is the process of separating the digital image into distinct region(s) possessing homogeneous properties. The main objective of image segmentation is to extract various features of the image that are used for analyzing, interpretation and understanding of images. Image segmentation is applied in various applications like medical imaging, shape detection, content-based image retrieval, robot vision, etc. Several techniques have been developed for image segmentation such as pixel-based segmentation, edge based segmentation and region based segmentation. In this paper, segmentation technique is defined using the edge detection and morphological operations. Edge detection is done using Fuzzy Canny method for better output. After detecting the edges of image, segmentation is done using morphological operation. This gives better results.
Image Compression is useful technique through which we can reduce the storage space of images which will helpful to increase storage and transmission process with saving the channel bandwidth. There are number of algorithms available for lossy and lossless image compression. As lossy technique is not reversible so it is beneficial to use lossless technique to recover the original image. In this paper we analyze different types of existing method of lossless image compression. The methods which are discussed are Run Length Encoding, Huffman coding, Arithmetic, and LZW with its performance.
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