Morphological Spot Detection and Analysis for Microarray Images
Manjunath S.S1, Shreenidhi B.S2, Nagaraja J3, Pradeep.B.S4
1Dr. Manjunath S.S, Department of Information Science, Dayananda Sagar Academy of Technology and Management, Bangalore (Karnataka), India.
2Shreenidhi B.S, Department of Computer Science, Dayananda Sagar College of Engineering, Bangalore (Karnataka), India.
3Nagaraja J, Assistant Professor, Department of Computer Science, Dayananda Sagar College of Engineering, Bangalore (Karnataka), India.
4Dr. Pradeep B.S, Department of Computer Science, Rajarajeshwari College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 15 April 2013 | Revised Manuscript received on 22 April 2013 | Manuscript Published on 30 April 2013 | PP: 189-193 | Volume-2 Issue-5, April 2013 | Retrieval Number: E0721042413/13©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: DNA microarray technology has promised a very accelerating research inclination in recent years. There are numerous applications of this technology, including clinical diagnosis and treatment, drug design and discovery, tumor detection, and in the environmental health research. Enhancement is the major pre-processing step in microarray image analysis. Microarray images when corrupted with noise may drastically affect the subsequent stages of image analysis and finally affects gene expression profile. Spot detection is the major preprocessing stage in microarray image segmentation. In this paper, morphological approach to detect spots in a subgrid. The proposed approach consists of two phases. First phase is morphological preprocessing, second phase includes spot detection model uses bottomhat transform. Experiments on Stanford, TBDB and UNC database illustrate robustness of the proposed approach in the presence of noise, artifacts and weakly expressed spots. Experimental results and analysis illustrates the performance of the proposed method with the contemporary methods discussed in the literature.
Keywords: Morphology, Dilation, Erosion, Bottomhat Transform.
Scope of the Article: Image Processing and Pattern Recognition