A New Approach of Content Based Image Retrieval Using Color and Texture Features

The dramatic development of multimedia technology, and the use of image capturing equipment have increased the number of images worldwide which are needed to be available. For this purpose, there are many general processes of image retrieval of which are Text based image retrieval (TBIR), Content based images retrieval (CBIR). While retrieving images using text-based approach, all the images are needed to be annotated manually which is time consuming. To be get the image retrieval process rid of this complexity content based approach was introduced. There are several processes of CBIR system. Here a new method of CBIR has been proposed which is based on both texture features and color features. Here, HSV histogram, Autocorrelogram, and color moment have been used to extract the color features. On the other hand, for the purpose of the extraction of texture features, Wavelet transformation, and Gabor wavelet transformation have been used. For implementing the process, a GUI has been designed at first. For every category searching, the elapsed time is calculated, and compared with the existing methods.