A SURVEY OF CBIR TECHNIQUES AND SEMANTICS

作者：Dr H B KEKRE; Mr DHIRENDRA MISHRA; Mr ANIRUDH KARIWALA

来源：International Journal of Engineering Science and Technology, 2011.

• CBIR
• Feature vectors
• Similarity measurement
• Performance Measure
• Precision
• Recall
• LIRS
• LSRR
• MSE.

Content based image retrieval is an important research area in image processing, witha vast domain of applications like recognition systems i.e. face, finger, biometrics etc. This paper provides extensive review of various latest research work and methodologies applied in the field of CBIR. The CBIR system has been reviewed based on its fundamental components i.e. feature extraction methods in frequency and spatial domain, similarity measures like distances e.g. Euclidean Distance, sum of Absolute difference, MSE and classifiers e.g. Neural network classifier and algorithmic performance measures like precision, recall, LIRS (Length of Initial Relevant String of Image), LSRR (Length of String to Recover All Relevant Images), FAR, FRR and FTC. Use of these parameters in various applications of CBIR has been discussed and compared. These parameters play very crucial role in deciding the overall performance of the any CBIR system. There are still lots of research on in the field of content-based image retrieval for its more faster and accurate behavior.

• 出版日期2011