Get High Precision in Content-Based Image Retrieval using Combination of Color, Texture and Shape Features

Content-based image retrieval has become hot topic for research. Only color, texture or shape feature extraction cannot give high precision. To get high precision, this paper proposes a new content-based image retrieval method that uses combination of color, texture and shape feature. The color moment will be calculated to extract the color feature, where the image will be converted from RGB to HSV color space. The Ranklet Transform is performed to extract the texture feature, where the image will be in gray-scale. The Hough Transform is performed to extract the shape feature, where the image will be in gray-scale. Experiment results show that using combination of color, texture and shape feature to compare and retrieve image is more accurate than using one of them only.