S. Venkannah Mechanical and Production Engineering DepartmentFaculty of Engineering Robotics Technology MECH 4041 B.Eng (Hons.) Mechatronics 1UNIVERSITY OF MAURITIUS FACULTY OF ENGINEERING ROBOTICS TECHNOLOGY – MECH 4041 B. Eng (Hons.) Mechatronics Level 4 Prepared by S. Venkannah 1.0 Image segmentation: The first step in image analysis generally is to segment the image. Segmentation subdivides an image into its constituents parts or objects. The level to which this subdivision is carried depends on the problem being solved. That is, segmentation should stop when the objects of interest in an application have been isolated. For example, in autonomous air to ground target acquisition applications,, interest lies, among other things, in identifying vehicles on a road. The first step is to segment the road from the image ad then to segment the potential vehicles. There is no point in carrying segmentation below this scale., nor is there any need to attempt segmentation of image components that lie outside the boundaries of the road. Segmentation. Segmentation is a general term which applies to various methods of data reduction. In segmentation, the objective is to group areas of an image having similar characteristics or features into distinct entities representing parts of the image. Segmentation is the process that subdivides a sensed scene into its constituent parts or objects. Segmentation is one of the most important elements of an automated vision system because it is at this stage of processing that objects are extracted from a scene for subsequent recognition and analysis. Segmentation algorithms are generally based on one of two basic principles: discontinuity and similarity. The principal approach in the first category is based on edge detection; the principal approaches in the second category are based on thresholding and region growing. For example, boundaries (edges ) or regions (areas) represent two natural segments of an image. There are many ways to segment an image. Image segmentation: Image segmentation refers to the partition of an image into a set of regions that cover it. The goal in many tasks is for the regions to represent meaningful areas of the image such as : crops, urban areas, and forests of a satellite image. 6 Regions might be sets of border pixels grouped into such structures as line segments and circular arc segments 6 Regions may also be defined as groups of pixels having both a border and a particular shape such as a circle or ellipse or polygon 6 When image do not cover whole image, segmentation can consider foreground regions of interest and background regions to be ignored. Objectives:
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