A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Image Compression Based on Visual Saliency at Individual Scales
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Saliency detection for content-aware image resizing
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
A case-based reasoning approach for detection of salient regions in images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
High level describable attributes for predicting aesthetics and interestingness
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Global contrast based salient region detection
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Salient object detection by composition
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
| Hi-index | 0.00 |
Color is the most dominant feature used by the human brain to perceive an image region to be salient. Since size, shape, location and colors of salient objects vary widely, a fuzzy rule based system is proposed in this paper which uses color proximity, color spread, connected components and presence of a face as linguistic variables. These rules are learned using a genetic algorithm. The colorspace used is the CIELab colorspace which closely conforms with human perception of colors. A publicly available image dataset is used for training and testing the system. Comparisons with existing state-of-the-art methods in terms of precision, recall and F-Measure have been presented.