Squid Species Matching using Fuzzy Edge Based Algorithm
K. Himabindu1, Raju Anitha2, K.Sekar3, G.Vasavi4

1K. Himabindu , Associate Professor, Computer Science., Dept. of Computer Science, Sri Venkateswara College of Engineering, Tirupati, (AP) India.
2Raju Anitha, Assoc. Prof., Dept. of Computer Science and Engineering in Koneru Lakshmaiah Education Foundation, (AP) India.
3K.Sekar, Professor, Departmentsof Computer Science and Engineeering, S.V. College of Engineering, Tirupati, (AP) India.
4G.Vasavi, Assistant Professor, department of Computer Science and Engineering at Hyderabad Institute of Technology and Management, Hyderabad, (AP) India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on March 30, 2020. | PP: 3887-3891 | Volume-8 Issue-6, March 2020. | Retrieval Number: E6759018520/2020©BEIESP | DOI: 10.35940/ijrte.E6759.038620

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Abstract: In the area of Commercial species identification, Squids species identification is significant because Squids plays an important role in Marine food chain. The identification of Squid species requires information about their morphometric features. Body shape feature is one of the important morphometric features for Squids. Hence, we consider only shape feature of Squid. Edge detection is an important technique to extract the shape feature for Squid images. Squid images contains uncertainty because of the problems occurs in the data acquisition and its complex structure. Hence, to avoid above mentioned uncertainties occurs in the Squid images consider Fuzzy edge map. In this work Fuzzy Edge Based Retrieval Algorithm is proposed for the query based Squid image retrieval from Squid’s database. In the process of Fuzzy Edge Based Retrieval Algorithm, first Fuzzy Edge map is constructed for Squid images later the Euclidian distance similarity measure performs between Query image and the candidate images in the Squids database. Based on the similarity metric the relevant Squid images are matched with query image are retrieved. The performance of proposed algorithm analysed with precision recall graphs.
Keywords: Squid Species, Shape Extraction, Fuzzy Edge Map, Similarity Matching, Performance Evaluation.
Scope of the Article: Parallel and Distributed Algorithms.