Digital Image Segmentation Process

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INTRODUCTION Chapter 1 A digital image is a numeric representation of a 2-dimensional image. It is represented as a finite set of some digital values, which are picture elements/pixels. Pixel values represent grey levels, colors, intensities, heights etc. Also, a digital image is an estimation of a real scenario, which is explained by digitization. Digital Image Processing, as name expresses, is processing applied on digital images. It includes a number of techniques which are used to manipulate the digital images by computers. The question arises is that what is the need of processing the digital images? The answer is because the image received from the sensors on the satellite can contain some flaws or deficiencies like…show more content…
Typically, image segmentation is used to situate boundaries and objects in images. In more precise, it is the process where assignment of a label to each and every pixel in an image is done such that pixels having same label share some visual characteristics. As a result, a set of different segments that forms the entire image is obtained. Each pixel has some computed property, or some characteristics, like intensity, color, texture, etc. All the processing operations usually aim to recognize a better object of interest i.e., find some desirable local features that may be distinguished from the other objects in the image from the background. In the next step, each pixel is checked to find whether it is among the objects of interest. This operation develops a binary image. A pixel is of value 1 if it belongs to set of object of interest; otherwise it is of 0. After segmentation, it is defined that one pixel belongs to one object. The image is partitioned into regions and the discontinuities are obtained as the boundaries between the regions. The types of image segmentations…show more content…
The first chapter describes the background, problem statement and objectives of the study. The second chapter discusses some related works on blood vessel segmentation techniques and denoising approaches. Chapter three provides detail information of the methodology and tools used in this thesis. The theory of ICA and relative entropy based thresholding approach are described in this chapter along with the proposed approach. It also provides information about data types used for this study and the adapted model. In chapter four obtained results are presented and evaluation of the applied methods is discussed. In chapter five the summary and conclusions of this study are

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