| Full text | |
| Author(s): |
Ferraz, Carolina Toledo
[1]
;
Pereira Junior, Osmando
[1]
;
Rosa, Marcos Verdini
[1]
;
Gonzaga, Adilson
[1]
Total Authors: 4
|
| Affiliation: | [1] Univ Sao Paulo, Dept Elect Engn, BR-13566590 Sao Carlos, SP - Brazil
Total Affiliations: 1
|
| Document type: | Journal article |
| Source: | INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE; v. 28, n. 8 DEC 2014. |
| Web of Science Citations: | 8 |
| Abstract | |
Bag of Features (BoF) has gained a lot of interest in computer vision. Visual codebook based on robust appearance descriptors extracted from local image patches is an effective means of texture analysis and scene classification. This paper presents a new method for local feature description based on gray-level difference mapping called Mean Local Mapped Pattern (M-LMP). The proposed descriptor is robust to image scaling, rotation, illumination and partial viewpoint changes. The training set is composed of rotated and scaled images, with changes in illumination and view points. The test set is composed of rotated and scaled images. The proposed descriptor more effectively captures smaller differences of the image pixels than similar ones. In our experiments, we implemented an object recognition system based on the M-LMP and compared our results to the Center-Symmetric Local Binary Pattern (CS-LBP) and the Scale-Invariant Feature Transform (SIFT). The results for object classification were analyzed in a BoF methodology and show that our descriptor performs better compared to these two previously published methods. (AU) | |
| FAPESP's process: | 11/18645-2 - Dynamic characteristics of human eye for biometric applications |
| Grantee: | Adilson Gonzaga |
| Support Opportunities: | Regular Research Grants |