Image Retrieval Based on Content Using Color Feature

In various application domains such as education, crime prevention, commerce, and biomedicine, the volume of digital data is increasing rapidly. The problem appears when retrieving the information from the storage media. Content-based image retrieval systems aim to retrieve images from large image databases similar to the query image based on the similarity between image features. This book presents a CBIR system that uses the color feature as a visual feature to represent the images. Images are selected from the WANG database that is widely used for CBIR performance evaluation. Ranklet Transform is used to make the image invariant to rotation and any image enhancement operations. For the resulting ranklet images, the color feature is extracted by calculating the color moments. The color moments are invariant to rotation and scaling. This is a benefit of our system. To speed up the retrieval time, images are clustered according to their features using k-means clustering algorithm.