Edge Detection using Mathematical Morphology for Gridding of Microarray Image
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Abstract
A Deoxyribonucleic Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface, such as glass, plastic or silicon chip forming an array. The DNA microarray image analysis includes three tasks: gridding, segmentation and intensity extraction. The size and shape of the spots is different from each other and some spots have low density to make them very difficult to detect, generating errors in processing the microarray images. In this paper, we present a method to eliminate such obstacles by sensing their edges using mathematical morphology. Application of edge detection technology on separating spots from the background decreases the probability errors and gives more accurate information about the status of the spots. After the guided spots are found, the correct grid can be generated. The proposed method is compared with some existing edge detection methods. The experimental results show that the proposed algorithm has found the edges of spots of microarray image more accurately.
Keywords: Microarray, Image Processing, Edge detection, Mathematical Morphology.
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