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Impact on Image Retrieval with Successive Truncation of DCT
by
N S T Sai,
R C Patil
| International Journal of Applied Information Systems |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 2 - Number 1 |
| Year of Publication: 2012 |
| Authors: N S T Sai, R C Patil |
10.5120/ijais12-450231
|
N S T Sai, R C Patil . Impact on Image Retrieval with Successive Truncation of DCT. International Journal of Applied Information Systems. 2, 1 ( May 2012), 1-10. DOI=10.5120/ijais12-450231
@article{
10.5120/ijais12-450231,
author = {
N S T Sai,
R C Patil
},
title = { Impact on Image Retrieval with Successive Truncation of DCT },
journal = {
International Journal of Applied Information Systems
},
issue_date = { May 2012 },
volume = { 2 },
number = { 1 },
month = { May },
year = { 2012 },
issn = { 2249-0868 },
pages = {
1-10
},
numpages = {9},
url = {
https://www.ijais.org/archives/volume2/number1/122-0231/
},
doi = { 10.5120/ijais12-450231 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:44:07.439793+05:30
%A N S T Sai
%A R C Patil
%T Impact on Image Retrieval with Successive Truncation of DCT
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 2
%N 1
%P 1-10
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The process of digitization does not in itself make image collections easier to manage. Some form of cataloguing and indexing is still necessary – the only difference being that much of the required information can now potentially be derived automatically from the images themselves. The extent to which this potential is currently being realized is discussed below. This paper presents the method developed to search and retrieve the similar image using feature vector computed from the image which is truncated successively using DCT. Truncated image coefficients are reducing after each level. So the impact of this successively truncated DCT on the retrieving the image is discussed in this paper . Gray scale image, RGB color image and YCbCr color image is used to compute the feature vector. So we can compare the result of these three types of color plane for the proposed method. Similarity between the query image and database image measured here by using simple Euclidean distance and Bray Curtis distance. The average precision and average recall of each image category and overall average precision and overall average recall is considered for the performance measure.
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Index Terms
Computer Science
Information Sciences
Keywords