Preattentive processing in vision
Computer Vision, Graphics, and Image Processing
Local operators to detect regions of interest
Pattern Recognition Letters - special issue on pattern recognition in practice V
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Finding salient regions in images: nonparametric clustering for image segmentation and grouping
Computer Vision and Image Understanding - Special issue on content-based access for image and video libraries
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object-based visual attention for computer vision
Artificial Intelligence
Content-Based Image Retrieval Based on ROI Detection and Relevance Feedback
Multimedia Tools and Applications
Region-based representations of image and video: segmentation tools for multimedia services
IEEE Transactions on Circuits and Systems for Video Technology
Information Sciences: an International Journal
| Hi-index | 0.01 |
Many computer vision applications, such as object recognition and content-based image retrieval could function more reliably and effectively if regions of interest were isolated from their background. A new method for regions of interest extraction from color image based on visual saliency in HSV color space is proposed in this paper. Color saliency is calculated by a two-dimensional sigmoid function using the saturation component and brightness component, and we can identify regions with vivid color. Discrete Moment Transform (DMT)-based saliency can determine large areas of interest. A visual saliency map is obtained by combining color saliency and DMT-based saliency, which is denoted the S image. A criterion for the local homogeneity called the E image is calculated in the image. Based on S image and E image, the high visual saliency object seed points set and low visual saliency object seed points set are determined. The seeded regions growing and merging are used to extract regions of interest. Experimental results demonstrate the effectiveness and efficiency of the method for the natural color images.