Name
Title | ||
|---|---|---|
An efficient color descriptor based on global and local color features for image retrieval |
Abstract | ||
|---|---|---|
In the context of content-based image retrieval (CBIR) problem, an image is represented by feature vectors called descriptors, whose efficiency is essential to obtain a good performance in the image indexing and retrieval tasks. In this paper, we propose an algorithm to obtain an efficient color-based descriptor, which is a combination of Color Correlogram (CC) and Dominant Color (DC). The color-based descriptors, such as Histogram Intersection (HI) and DC take into account the global distribution of color in an image, while CC takes into account the local color distribution. So the combination of global and local color distribution provides a good image description. By its design, the proposed descriptor is more compact compared with the CC descriptor, which allows reducing computational complexity. Using the Average Retrieval precision (ARP) with different factors the effectiveness of the proposed descriptor is evaluated and compared with the conventional color-based descriptors, such as HI, CC and DC. The image database used in this work contains 500 images with 25 categories randomly selected from the Corel Dataset. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICEEE.2013.6676028 | Electrical Engineering, Computing Science and Automatic Control |
Keywords | Field | DocType |
computational complexity,content-based retrieval,image colour analysis,image representation,image retrieval,indexing,CBIR problem,Corel dataset,average retrieval precision,color correlogram,color descriptor,color-based descriptor,computational complexity,content-based image retrieval problem,dominant color,feature vectors,global color distribution,global color features,histogram intersection,image indexing task,image representation,image retrieval task,local color distribution,local color features,CBIR,color correlogram,color-based descriptor,dominant color,histogram intersection,image indexing,image retrieval | Computer vision,Image gradient,Pattern recognition,Color histogram,Image texture,Computer science,Artificial intelligence,Histogram equalization,Color normalization,Color quantization,Color image,Visual Word | Conference |
ISBN | Citations | PageRank |
978-1-4799-1460-9 | 0 | 0.34 |
References | Authors | |
0 | 9 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Atoany N. Fierro-Radilla | 1 | 2 | 1.44 |
| Mariko Nakano-Miyatake | 2 | 144 | 29.99 |
| Héctor Pérez-Meana | 3 | 48 | 15.66 |
| Manuel Cedillo-Hernandez | 4 | 68 | 10.06 |
| Francisco García-Ugalde | 5 | 33 | 8.12 |
| Fierro-Radilla, A.N. | 6 | 0 | 0.34 |
| Nakano-Miyatake, M. | 7 | 2 | 2.06 |
| Perez-Meana, H. | 8 | 1 | 1.71 |
| Cedillo-Hernandez, M. | 9 | 0 | 0.34 |