| Full text | |
| Author(s): |
Ponti, Moacir
;
Picon, Camila T.
;
IEEE
Total Authors: 3
|
| Document type: | Journal article |
| Source: | 2015 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING (ICASSP); v. N/A, p. 5-pg., 2015-01-01. |
| Abstract | |
Image classification often require preprocessing and feature extraction steps that are directly related to the accuracy and speed of the whole task. In this paper we investigate color features extracted from low resolution images, assessing the influence of the resolution settings on the final classification accuracy. We propose a border-interior classification extractor with a logarithmic distance function in order to maintain the discrimination capability in different resolutions. Our study shows that the overall computational effort can be reduced in 98%. Besides, a fast bitwise quantization is performed for its efficiency on converting RGB images to one channel images. The contributions can benefit many applications, when dealing with a large number of images or in scenarios with limited network bandwidth and concerns with power consumption. (AU) | |
| FAPESP's process: | 11/22749-8 - Challenges in exploratory visualization of multidimensional data: paradigms, scalability and applications |
| Grantee: | Luis Gustavo Nonato |
| Support Opportunities: | Research Projects - Thematic Grants |
| FAPESP's process: | 10/19159-1 - Evaluation of color descriptors in natural images at various resolutions aided by a visualization tool |
| Grantee: | Camila Tatiana Picon |
| Support Opportunities: | Scholarships in Brazil - Scientific Initiation |