Cuckoo Search based Soft computing Approach for Quality Analysis of White Poppy Seeds

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Goutam Das


Poppy seeds are found to be a strictly monitored crop which is because of its narcotic effects. However the use of poppy seeds in food,
industrial and medical purpose opens the door for its survival. It generates a good amount of foreign currency for the producing country. Due to
its high value its quality should also be assured. In this study nature is applied for benefit of nature, that is nature-inspired metaheuristic
algorithms, that is Cuckoo Search (CS) and Particle Swarm Optimization (PSO) have been used to check and monitor the quality of the white
poppy seeds. CS is used in the preprocessing stage of the approach, whereas PSO is used for segmentation and final outcome. Basically CS is
used to enhance the image quality, which helps to further process the image in later stages. Combination of these two approaches is quite new,
but the results are very good. Visual results imply that impurities in terms of black seeds within white seeds can be successfully recognized
through computer vision analysis.

Keywords- Poppy seeds, Computer vision, image enhancement, Cuckoo Search, L´evy flight, Particle Swarm Optimization, Segmentation,


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