| dc.description.abstract | The differences in color, shape, and texture characteristics between each animal cause difficulties in animal image retrieval. Therefore, specified technique is needed to obtain pattern from each animal’s feature so that image retrieval might works properly. One of the techniques to obtain the pattern done by feature extraction. This research tries to develop image extraction method in Content Based Image Retrieval approach by using three image visual features (color, shape, texture). In this research, Fuzzy Color Histogram (FCH) for color feature extraction is used through computing the membership function using Cauchy function. In FCH, one color may belong to two bins histogram or more with different membership functions. Then, shape feature is extracted using edge direction histogram, where each image is processed using Sobel edge detection, and then the direction is mapped into a defined bin histogram. For texture feature extraction, the process uses co-occurrence matrix with computing the values of energy, moment, entropy, maximum probability, contrast, correlation and homogeneity. Similarity value between image query and images in database is computed based on its features, those are color, shape, texture, and its combination. Recall and precision value resulted in this research shows the largest average precision value is obtained from searching process using index combination (color, shape, texture) of feature extraction. Keywords: feature extraction, Fuzzy Color Histogram, edge direction histogram, co-occurrence matrix | id |
