Image retrieval using the combination of text-based and content-based algorithms

Image retrieval is an important research field, which has received great attention in the last decades. The main purpose of research in this field is to improve the process of finding the desired image in the large and variable database. In this paper, we present an approach for the image retrieval based on the combination of text-based and content-based features. For text-based features, keywords and for content-based features, color and texture features have been used. A query in this system contains some keywords and an input image. At first, the images are retrieved based on the input keywords. Then, visual features are extracted to retrieve ideal output images. For extraction of color features, we have used color moments and for texture, we have calculated color co-occurrence matrix for each Red, Blue and gray component. The COREL image databas have been used for our experimental results. The experimental results show that the performance of the combination of both text-based and content-based features is much higher than each of them, which is applied separately.