DocumentCode :
2735774
Title :
CoLDImage: Contrast and luminance distribution for content-based image retrieval
Author :
Su, Qingkun ; Huang, Yan ; Peng, Jingliang
Author_Institution :
Shandong Provincial Key Lab. of Software Eng., Shandong Univ., Jinan, China
fYear :
2011
fDate :
21-23 Oct. 2011
Firstpage :
143
Lastpage :
146
Abstract :
With the increasing volumes of digital image data and the rapid development of internet technologies, it becomes vital to efficiently and accurately retrieve inquired images from the vast available data resources. In this context, content-based image retrieval has been intensively researched in the past decades. In this work, we propose to use contrast and luminance distribution, abbreviated as CoLD, to describe the textural and luminance characteristics of a digital image. The CoLD descriptor is rotation invariant and scale invariant. In addition, it is very simple to compute. Experimental results demonstrate that, when used for content-based image retrieval, the CoLD descriptor yields significantly higher retrieval precision when compared with the classical methods including gray level co-occurrence matrix and Hu´s seven moment invariants.
Keywords :
content-based retrieval; image colour analysis; image retrieval; matrix algebra; CoLDImage; Hu seven moment invariants; Internet; content-based image retrieval; contrast distribution; digital image data; gray level cooccurrence matrix; luminance distribution; Image color analysis; Image retrieval; Measurement; Shape; Three dimensional displays; Vectors; Wheels; Hu´s seven moment invariants (HSMI); content-based image retrieval (CBIR); contrast and luminance distribution (CoLD); gray level co-occurrence matrix (GLCM);
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Analysis and Signal Processing (IASP), 2011 International Conference on
Conference_Location :
Hubei
Print_ISBN :
978-1-61284-879-2
Type :
conf
DOI :
10.1109/IASP.2011.6109015
Filename :
6109015
Link To Document :
بازگشت