Improving CBIR accuracy using convolutional neural network for feature extraction

Content Based Image Retrieval (CBIR) becomes a very challenging taks due to the rapid growth in multimedia content and its visual complexity. From query by image to retrieval of relevant images, CBIR has different phases. However, features extraction of images is one of the important phases. Recently Convolutional Neural Network (CNN) shows good results in the field of computer vision due to the ability of extraction features from the images. This paper introduces CNN for features extraction from images, in CBIR system. Euclidean distance is used for association among query and stored images using the extracted features. Performance of the proposed work is evaluated using precision. The proposed work shows improved results as compared to the existing works.