Title :
Image retrieval based on edge classification method in BTC-VQ compressed domain
Author :
Sarshar, Mohammad Reza ; Ghahroudi, Mahdi Rezaei
Author_Institution :
Azad Univ., Karaj
Abstract :
Because of high volume of graphic information, retrieval of compressed images is one of the needs of information era. One of the rapid methods for image compression which has the capability to maintain important information of images for retrieval is block truncation coding (BTC). In this article a new method for retrieval of images compressed by BTC has been provided. In our approach, we use some classified patterns, derived from BTC method as a retrieval feature. This method has been examined on a database consisting of 9983 images with different contents and its results have been compared with similar methods.
Keywords :
block codes; edge detection; image classification; image coding; image retrieval; vector quantisation; BTC-VQ compressed domain; block truncation coding; edge classification; image compression; image retrieval; vector quantisation; Graphics; Histograms; Image coding; Image databases; Image retrieval; Image storage; Information retrieval; Intelligent systems; Spatial databases; Transform coding;
Conference_Titel :
Intelligent and Advanced Systems, 2007. ICIAS 2007. International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4244-1355-3
Electronic_ISBN :
978-1-4244-1356-0
DOI :
10.1109/ICIAS.2007.4658575
