Name
Abstract | ||
|---|---|---|
This paper proposes a new simple method of Discrete Cosine Transform (DCT) feature extraction that is used to accelerate the speed and decrease the storage needed in the image retrieving process. Image features are accessed and extracted directly from JPEG compressed domain. This method extracts and constructs a feature vector of histogram quantization from partial DCT coefficient in order to count the number of coefficients that have the same DCT coefficient over all image blocks. The database image and query image is equally divided into a non overlapping 8X8 block pixel, each of which is associated with a feature vector of histogram quantization derived directly from discrete cosine transform DCT. Users can select any query as the main theme of the query image. The retrieved images are those from the database that bear close resemblance with the query image and the similarity is ranked according to the closest similar measures computed by the Euclidean distance. The experimental results are significant and promising and show that our approach can easily identify main objects while to some extent reducing the influence of background in the image and in this way improves the performance of image retrieval. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/CW.2009.61 | CW |
Keywords | Field | DocType |
dct histogram quantization,partial dct coefficient,feature extraction,query image,histogram quantization,image feature,efficient image retrieval,image retrieval,dct coefficient,feature vector,image block,database image,image features,histograms,quantization,discrete cosine transform,data mining,statistical analysis,euclidean distance,data compression | Top-hat transform,Computer vision,Pattern recognition,Feature detection (computer vision),Feature (computer vision),Computer science,Image retrieval,Feature extraction,Artificial intelligence,Trellis quantization,Quantization (image processing),Image histogram | Conference |
Citations | PageRank | References |
7 | 0.53 | 6 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aamer Mohamed | 1 | 7 | 0.53 |
| F. Khellfi | 2 | 7 | 0.53 |
| Ying Weng | 3 | 96 | 9.27 |
| Jianmin Jiang | 4 | 985 | 81.39 |
| Stan Ipson | 5 | 12 | 2.03 |