FUZZY EDGE IMAGE MATCHING ALGORITHM FOR SQUID SPECIES IDENTIFICATION

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Published: Oct 31, 2020
DOI: https://doi.org/10.22452/mjs.vol39no3.8
Keywords:
Squid species Shape extraction Fuzzy Edge Map similarity matching Performance evaluation

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K Hima bindu
Sri Padmavati Mahila Visvavidyalayam (Women’s University)
S. Jyothi
Sri Padmavati Mahila Visvavidyalayam (Women’s University)
D.M. Mamatha
Sri Padmavati Mahila Visvavidyalayam (Women’s University)

Abstract

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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How to Cite
bindu, K. H., Jyothi, S., & Mamatha, D. (2020). FUZZY EDGE IMAGE MATCHING ALGORITHM FOR SQUID SPECIES IDENTIFICATION. Malaysian Journal of Science, 39(3), 95–103. https://doi.org/10.22452/mjs.vol39no3.8
Issue
Vol 39 No 3 (2020): October
Section
Original Articles

Licensee MJS, Universiti Malaya, Malaysia. This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

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