%0 Journal Article %1 noauthororeditor %A Bhargavi, Syed Shareefunnisa M %D 2017 %J International Journal of Trend in Scientific Research and Development %K Computer Engineering Hybrid Otsu Segmentation algorithm %N 1 %P 730-735 %T Solving Image Thresholding Problem Using Hybrid Algorithm %U http://www.ijtsrd.com/engineering/computer-engineering/7021/solving-image-thresholding-problem-using-hybrid-algorithm/syed-shareefunnisa- %V 2 %X Thresholding is a reputed image segmentationtechnique used to obtain binary image from the gray levelimage. In this paper, histogram based bi'“level and multi-levelsegmentation is proposed using Improved Particle SwarmOptimization (PSO) and Enhanced Bacterial ForagingOptimization (EBFO) based hybrid algorithm. The optimalthresholds for input images are attained by maximizing Otsu'sbetween class variance function. The performance of proposedmethod is demonstrated on four benchmark images andcompared with the existing PSO and BFO algorithms. Anassessment between HA, PSO, and BFO is carried usingprevailing parameters such as objective function, convergence rate, PSNR, and DSSIM. Syed Shareefunnisa | M Bhargavi"Solving Image Thresholding Problem Using Hybrid Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7021.pdf http://www.ijtsrd.com/engineering/computer-engineering/7021/solving-image-thresholding-problem-using-hybrid-algorithm/syed-shareefunnisa-

@article{noauthororeditor, abstract = {Thresholding is a reputed image segmentationtechnique used to obtain binary image from the gray levelimage. In this paper, histogram based bi'“level and multi-levelsegmentation is proposed using Improved Particle SwarmOptimization (PSO) and Enhanced Bacterial ForagingOptimization (EBFO) based hybrid algorithm. The optimalthresholds for input images are attained by maximizing Otsu'sbetween class variance function. The performance of proposedmethod is demonstrated on four benchmark images andcompared with the existing PSO and BFO algorithms. Anassessment between HA, PSO, and BFO is carried usingprevailing parameters such as objective function, convergence rate, PSNR, and DSSIM. Syed Shareefunnisa | M Bhargavi"Solving Image Thresholding Problem Using Hybrid Algorithm" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-1 , December 2017, URL: http://www.ijtsrd.com/papers/ijtsrd7021.pdf http://www.ijtsrd.com/engineering/computer-engineering/7021/solving-image-thresholding-problem-using-hybrid-algorithm/syed-shareefunnisa- }, added-at = {2018-09-01T11:52:12.000+0200}, author = {Bhargavi, Syed Shareefunnisa M}, biburl = {https://www.bibsonomy.org/bibtex/2460c29777c28159347474c31f8878ea9/ijtsrd}, interhash = {3f84197b1060f1a98fe7c4c17b68ff06}, intrahash = {460c29777c28159347474c31f8878ea9}, issn = {2456-6470}, journal = {International Journal of Trend in Scientific Research and Development}, keywords = {Computer Engineering Hybrid Otsu Segmentation algorithm}, language = {English}, month = dec, number = 1, pages = {730-735}, timestamp = {2018-10-02T11:01:27.000+0200}, title = {Solving Image Thresholding Problem Using Hybrid Algorithm }, url = {http://www.ijtsrd.com/engineering/computer-engineering/7021/solving-image-thresholding-problem-using-hybrid-algorithm/syed-shareefunnisa-}, volume = 2, year = 2017 }