Query images are processed in the similar way and similarity matching between query and database images is done through Hybrid Graph method. Features are extracted from these images and stored into the database. Approximately one to two thousand images are stored in the database. Images are annotated automatically without human intervention. For improving the speed of image retrieval process using TBIR, we are implementing automatic annotation technique.
We are using RGB to Lab conversion for color feature extraction, Modified Canny edge detection algorithm with variable sigma for shape feature extraction, Framelet transform method for texture feature extraction.
To improve the accuracy, we are using combination of most efficient feature extraction algorithms. The base of CBIR is to extract different image features, such as Color, Shape and Texture. In our research, we are combining Text Based Image Retrieval (TBIR) method with Content Based Image Retrieval (CBIR) method to enhance image retrieval. With the widespread use of image retrieval in various areas such as crime investigation, medical diagnosis, intellectual property rights, etc, today's need is to enhance the image retrieval process.
