A Brief Look at Image Segmentation

2140 WordsFeb 24, 20189 Pages
Mei wang, Xiao-Wei Wu, Hsiung-Cheng Lin, Jian-ping wang(2012) discussed the idea of following. Today medical images are widely used. To achieve a clear and noise free images Image-segmentation is essential point. In this paper a new image segmentation method that is proportion of foreground to background is used also called PFB. Using this method on human brain image we experiment the result that the number of iteration steps for the threshold T is reduced. Using this method over segmentation and discontinuities also can be avoided. Finally proposed a new method using both Thresholding image segmentation and edge detection segmentation algorithm based on the Proportion of Foreground to Background. After this the basic principal is define in this paper. Proportion of Foreground to Background Algorithm combine the traditional iterative algorithm. Anita Khanna, Dr. Manish Shrivastva(2012) In their paper they used unsupervised technique of segmentation which is simple and give satisfactory result. We use Ultrasound (US) images and apply unsupervised segmentation technique. There is a problem to segment Ultrasound image because of low contrast and high speckle noise. In this paper we use different unsupervised technique like Thresholding; k-means cluster technique and expectation maximization and compare all the result. Ultrasound images are texture feature image and expectation maximization (EM) technique gives best result of segmentation. In texture features images

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