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              <text>Development and Implementation of Algorithm for Image Preprocessing of Microorganism  </text>
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              <text>The digital revolution has changed most aspects of modern life. Nowhere has the change been more fundamental than in the field of microscopy. Researchers who use the microscope in their investigations have been newlineamong the pioneers who applied digital processing techniques to images. Vision is most powerful of the five senses of human being. Digitized visual information provides high impact on the subject. Digital image processing is concerned with the extraction of useful information from images. Visual newlineinformation from microscopic images of microorganisms is analyzed regularly. This has resulted in a need to understand and implement digital processing on microscopic images. The purpose of this thesis is to bring new digital image processing techniques for the noise removal of microscopic image of microorganisms. The digitized image processing includes image representation; improving image quality by removing noise; newlineand enhancing the quality of microscopic images. At the outset, the thesis elaborates on the concepts around microscopic images and their digital image processing. Various existing algorithms are studied for their efficacy. This thesis gives three different techniques of image processing based on the noise level in microscopic images. The thesis newlinedevelops the techniques of image processing through Simulation , which is well accepted tool in the field of engineering. MATLAB has been used in this study to simulate the image processing algorithms. The algorithms developed in the study will be helpful in everyday life through better analysis of microscopic images of microorganisms. The thesis is a contribution to the medical field with better analytical techniques. This research work overviews different image processing techniques used in the analysis of microscopic images and other type of images. After reviewing, use of microscopic imaging is presented. Special emphasis is on two types of noise called Gaussian noise and Impulsive noise is given.</text>
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              <text>Prasad, Smirty.</text>
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              <text>Christ(Deemed to be University)</text>
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              <text>Ganesan, N.</text>
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              <text>Open Access</text>
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              <text>&lt;a href="http://hdl.handle.net/10603/365042" target="_blank" rel="noreferrer noopener"&gt;http://hdl.handle.net/10603/365042&lt;/a&gt;</text>
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