Wavelet-Based Automated DNA Sizing of Fragments through AFM Image Processing
S. Anand1, B.Lakshmanan2, J. Murugachandravel3, K. Valarmathi4, Abhisha Mano5, N. Kavitha6

1S Anand, Professor, Department of ECE, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
2B.Lakshmanan, Asst. Professor (Sr. Grade), Department of CSE, MEPCO, Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
3J. Murugachandravel, Asst. Professor (Sl. Grade), Department of MCA, Mepco Schlenk Engineering College, Sivakasi (Tamil Nadu), India.
4K.Valarmathi, Senior Lecturer, Department of ECE, S. Vellaichamy Nadar Polytechnic College, Virudhunagar (Tamil Nadu), India.
5Abhisha Mano, Asst. Professor, Department of ECE, Rajas International Institute of Technology for Women (Tamil Nadu), India.
6N.Kavitha, Assistant Professor, Department of CSE, Saranathan Engineering College, Tiruchirapalli (Tamil Nadu), India.

Manuscript received on 18 June 2019 | Revised Manuscript received on 25 June 2019 | Manuscript published on 30 June 2019 | PP: 231-238 | Volume-8 Issue-5, June 2019 | Retrieval Number: D6167048419/19©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: Atomic Force Microscope (AFM) is a procedure to investigate the size of the DNA fragments. In this paper, an algorithm is presented to determine the DNA fragment size from images of DNA molecules. The previous automated approach that uses conventional filters fails to have multidirectional and multiscale properties. This automated approach implements an algorithm on multiscale shift invariant wavelet decomposition to recover the DNA fragments. In order to avoid erroneously evaluated fragments, this algorithm also includes thinning and threshold process on Euclidean norm of wavelet decomposition. The Euclidean norm of multilevel decomposition is able to control the noise whereas the hysteresis threshold ensures proper connectivity. Computer generated and real images are tested for different fragment size in various noise background. The DNA sizing of fragments is compared with already existing method. The improved performances are analyzed using Figure of Merit, accuracy, sensitivity, specificity and false positive rate.
Keywords: AFM Image, DNA Fragments, Wavelet Transform, DNA sizing

Scope of the Article: Image analysis