FUZZY EDGE IMAGE MATCHING ALGORITHM FOR SQUID SPECIES IDENTIFICATION
DOI:
https://doi.org/10.22452/mjs.vol39no3.8Keywords:
Squid species, Shape extraction, Fuzzy Edge Map, similarity matching, Performance evaluationAbstract
Abstract: The image features play important role in matching system. The effectiveness of these Squid species features depends on the global features. The identification of Squid species requires information of their morphology. Body shape is very useful to characterize the one species to another species. In Shape extraction, edge detection is an important aspect. Edge is an important visual feature and it represents visual information with a limited number of pixels. While considering the morphology of Squid, it can have uncertainty due to climatic conditions. Hence, in this study feature extraction is done by fuzzy edge map. In this paper we proposed Fuzzy Image Edge Image Matching Algorithm (FEIMA) for Squid species identification. Similarity metric is used for matching of query and the candidate images in the database and it finally displays the class of species. The proposed algorithm performance is calculated by using Average of precision and recall.
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