Content-Based Image Retrieval Using Customized Convolutional Neural Network

In today's world due to multimedia development, there is a huge image database. Content-Based Image retrieval (CBIR) is a widely used method for image retrieval from a large image database. Existing retrieval methods are based on the basic content of an image like color, Shape, and Texture. The system based on basic features requires more time for processing and provides less accuracy. To reduce time and improve accuracy we are proposing CBIR Using CNN in this paper. CNN is used for feature extraction and similarity measurement Hamming distance is used. In this technique, the user has to provide an image as an input query image. The similar images related to the query image are displayed as a result. The performances of a system are evaluated by precision and mean average precision (MAP). After comparing with existing methods, we found encouraging results that lead to improving accuracy.