Video image retrieval on the basis of subregional co-occurrence matrix texture features and normalised correlation

This paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore, this paper propo...

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Bibliographic Details
Main Authors: Kyuheon Kim, Seyoon Jeong, Byung Tae Chun, Jae Yeon Lee, Younglae Bae
Format: Conference Proceeding
Language:English
Subjects:
Content based retrieval
Entropy
Image databases
Image processing
Image retrieval
Image segmentation
Information retrieval
Multimedia databases
Software
Telecommunication computing
Online Access:Request full text
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Description
Summary:This paper proposes the simple and efficient image retrieval algorithm using subregional texture features. In order to retrieve images in terms of its contents, it is required to obtain a precise segmentation. However, it is very difficult and takes a long computing time. Therefore, this paper proposes a simple segmentation method, which is to divide an image into high and low entropy regions by using picture information measure (PIM). Also, in order to describe texture characteristics of each region, this paper suggests six different texture features produced on the basis of co-occurrence matrix. For an image retrieval system, a normalised correlation is adopted as a similarity function, which is not dependent on the range of each texture feature values. Finally, this proposed algorithm is applied to various images and produces competitive results.
ISSN:1062-922X
2577-1655
DOI:10.1109/ICSMC.1999.825386