Open AccessImproved Content-Based Image Retrieval Technique for Query Generation in Mobile Networks
Author(s) -
Bhupinder Kaur,
Madan Lal,
Jagroop Kaur
Publication year - 2020
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.f1626.089620
Subject(s) - computer science , upload , content based image retrieval , image retrieval , set (abstract data type) , feature (linguistics) , convolutional neural network , image (mathematics) , artificial intelligence , cloud computing , information retrieval , pattern recognition (psychology) , data mining , world wide web , linguistics , philosophy , operating system , programming language
Image database searching is in rapid growth with an advancement in multimedia technology. To manage these kinds of searches Content-Based Image Retrieval is an effective tool. In this paper, existing CBIR techniques are analyzed and a new technique has been proposed which works based on Region-Based Convolutional Neural Network (RCNN). In the proposed approach first of all image dataset is uploaded to cloud and features are stored in a storage. Then Query image is enhanced, uploaded and features are extracted. After this feature set is compared with dataset and matched images are extracted and ranked as the closest match. Using this proposed methodology, the accuracy and precision values are compared and validated and it is observed that the proposed methodology shows better results than the existing techniques.