Edge based Active Contour Model for Semi-transparent Images
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The book aims to provide an understanding on how to segment the images based on active contour based model. Interactive image segmentation algorithms are sensitive to the user inputs and are often unable to produce an accurate boundary with a small amount of user interaction. They frequently rely on laborious user editing to refine the segmentation boundary. The Gaussian Mixture Model method for image segmentation exhibits many desirable properties of an effective interactive image segmentation algorithm, including robustness to user inputs and different initializations, the ability to produce...
The book aims to provide an understanding on how to segment the images based on active contour based model. Interactive image segmentation algorithms are sensitive to the user inputs and are often unable to produce an accurate boundary with a small amount of user interaction. They frequently rely on laborious user editing to refine the segmentation boundary. The Gaussian Mixture Model method for image segmentation exhibits many desirable properties of an effective interactive image segmentation algorithm, including robustness to user inputs and different initializations, the ability to produce a smooth and accurate boundary contour, and the ability to handle topology changes, it fails to handle semi-transparent images.The aim of this work is to extract sharp and steep images by handling semi-transparent images. An edge based active contour model has been proposed in which the image edge is extracted smoothly with the Greedy algorithm. Additionally Distance Regularized Level set Evolution algorithm has also been used to handle the very steep contour of the images. I personally thank my god, colleagues and parents for their encouragement and support for the publication.
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