DocumentCode
2972472
Title
Image retrieval using the longest approximate common subsequences
Author
Wen-Chen Hu ; Schmalz, Mark S. ; Ritter, Gerhard X.
Author_Institution
Dept. of Comput. Sci. & Eng., Auburn Univ., AL
Volume
2
fYear
1999
fDate
36342
Firstpage
730
Abstract
Accurate and fast retrieval as well as efficient storage are two principal needs in an image database. Image search methods are the crucial factors in fulfilling these requirements. The longest common subsequence search method is mostly used in string-based image databases. However, a longest common subsequence does not always reveal the degree of difference between two strings. This research proposes a new image matching method, i.e., finding a longest approximate common subsequence of two strings. The experimental results show any image in the system can be precisely retrieved as long as each image has a unique image string, where accuracy of image retrieval depends on the level of query detail
Keywords
image matching; image retrieval; visual databases; image database; image matching; image retrieval; image search methods; longest approximate common subsequences; longest common subsequence search method; Computer science; Data engineering; Image databases; Image representation; Image retrieval; Image storage; Information retrieval; Los Angeles Council; Neural networks; Search methods;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia Computing and Systems, 1999. IEEE International Conference on
Conference_Location
Florence
Print_ISBN
0-7695-0253-9
Type
conf
DOI
10.1109/MMCS.1999.778575
Filename
778575
Link To Document