5.Image_segmentation

# Three important techniques that will be discussed are

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Unformatted text preview: e important techniques that will be discussed are 1 Thresholding 2 Region growing 3 Edge detection In some situations, such as industrial inspection applications, at least some measure of control over the environment is possible at times. In other applications, such as target acquisition, the system designer has no control of the environment. then, the usual approach is to focus on selecting the types of sensors most likely to enhance the objects of interest while diminishing the contribution of irrelevant image components. \ The main goal of image segmentation is to divide an image into parts that have a strong correlation with objects or areas of the real world depicted in the image \ Segmentation methods can be divided into three groups: thresholding, edge-based segmentation, and region based segmentation. \ Each region can be represented by its closed boundary, and each closed boundary describes a region. \ Image data ambiguity is one of the main segmentation problems, often accompanied by information noise. \ The more a priori information is available to the segmentation process, the better the segmentation results that can be obtained. Detection of discontinuities: Three basic types of discontinuities: points, lines, edges. In practice, the most common way to look for discontinuities is to run a mask through the image. For the 3*3 mask shown in Fig 1, this procedure involves computing the sum of products of the Faculty of Engineering Robotics Technology MECH 4041 2 B.Eng (Hons.) Mechatronics S. Venkannah Mechanical and Production Engineering Department coefficients. With the gray levels contained in the region encompassed by the mask, i.e. the response of the mask at any point in the image is R = w1z1 + w2z2 + ……+ w9z9 = Σ wizi w1 w2 w3 w4 w5 w6 w7 w8 w9 Fig 1: A general 3*3 mask. Where zi is the gray level of the pixel associated with mask coefficient wi. As usual the response of the mask is defined with respect to its center location. When the mask is centered on a boundary pixel, the response is computed by using the appropriate partial neighborhood. Point dete...
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## This document was uploaded on 03/12/2014 for the course MECHANICAL 214 at University of Manchester.

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