Image segmentation and its performance evaluation are very difficult but important problems in computer vision. A major challenge in segmentation evaluation comes from the fundamental conflict between generality and objectivity. The goal of image segmentation is to cluster pixels into salient image regions, i.e., regions corresponding to individual surfaces, objects, or natural parts of objects...

Image Segmentation based on Snake model is one of the hottest research fields of image processing. The Snake model integrates the characteristics of the lower layer of images and the prior knowledge of the upper layer. It can effectively implement medical image segmentation for the unique of medical images using the restriction of the lower layer of images to the prior knowledge of the upper la...

The objective of this work is to develop a segmentation model in order to remove the portion of lung for the treatment of certain illness such as lung cancer, and tumours. Image segmentation is the process of dividing an image into multiple parts. This method is vital to identify objects or other relevant information in digital images.During past few years we have gone across many region-based ...

this paper presents a new three-dimensional curvelet transform based dictionary learning for automatic segmentation of intraretinalcysts, most relevant prognostic biomarker in neovascular age-related macular degeneration, from 3d spectral-domain optical coherencetomography (sd-oct) images. in particular, we focus on the spectralis sd-oct (heidelberg engineering, heidelberg, germany) system, and...

Image segmentation means extracting the part of an image or any object.In digital image processing, image segmentation plays a vital role in the processing of images.Image segmentation is one of the most important steps leading to the analysis of processed image data. The goal of image segmentation is pattern recognition and image analysis besides simplifying the representation of an image whic...

I. Introduction Image Segmentation is a process which partitioned image into multiple unique regions, where region is set of similar pixels. If I is set of all image pixels, then by applying segmentation we get different-different unique regions like {R 1 ,R 2 ,R 3 ,..,R n } which when combined formed the image I. Many approaches have been proposed earlier which includes probabilistic graphical...

Image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as super pixels). The goal of segmentation is to simplify or change the representation of an image into something that is more meaningful and easier to analyze. Image segmentation is typically used to locate objects and boundaries (lines, curves, etc. ) in images. In this paper w...

The aim of this paper is improving the iris segmentation with the Contourlet transform. At first iris segmentation performed by canny edge detector and Hough Transform. By this approach some images don’t segmented properly, so we want to find a way to correct the image segmentation failures. Before applying edge detector, Contourlet transform applied for image denoising. By this approach, %100 ...

In this paper, we present a new framework for effective content-based image retrieval (CBIR) based on rectangular segmentation. In image segmentation, speed is more important than accuracy in CBIR. We propose a new rectangular approximate image segmentation to solve the problem. We also develop a significance function to reflect the importance of different position in image, and improve the seg...