Classification of Serranidae Species Using Color Based Statistical Features

Authors : Bilal İşçimen, Yakup Kutlu, Cemal Turan

Pages : 25-34

Doi:10.28978/nesciences.292352

View : 24 | Download : 15

Publication Date : 2017-02-08

Article Type : Research Paper

Abstract :In this study 6 species of Serranidae family insert ignore into journalissuearticles values(Epinephelus aeneus, Epinephelus caninus, Epinephelus costae, Epinephelus marginatus, Hyporthodus haifensis, Mycteroperca rubra); were classified by using a color based feature extraction method. A database which consists of 112 fish images was used in this study. In each image, a fish was located on a white background floor with the same position and the images were taken from different distances. A combination of manual processes and automatic algorithms were applied on images until obtaining colored fish sample images with a black background. Since the presented color based feature extraction method avoids including background, these images were processed by using an automatic algorithm in order to obtain a solid texture image from the fish and extract features. The obtained solid texture image was in HSV color space and used due to extract species-specific information from the fish samples. Each of the hue, saturation and value components of the HSV color space was used separately in order to extract 7 statistical features. Hence, totally 21 features were extracted for each fish sample. The extracted features were used within Nearest Neighbor algorithm and 112 fish samples from the 6 species were classified with an overall accuracy achievement of 86%.
Keywords : Classification, Serranidae family, HSV, color, texture