JOURNAL ARTICLE

An improved image segmentation algorithm for salient object detection

Abstract

Semantic object detection is one of the most important and challenging problems in image analysis. Segmentation is an optimal approach to detect salient objects, but often fails to generate meaningful regions due to over-segmentation. This paper presents an improved semantic segmentation approach which is based on JSEG algorithm and utilizes multiple region merging criteria. The experimental results demonstrate that the proposed algorithm is encouraging and effective in salient object detection.

Keywords:
Segmentation Salient Segmentation-based object categorization Image segmentation Computer science Artificial intelligence Scale-space segmentation Object (grammar) Object detection Pattern recognition (psychology) Computer vision Image (mathematics) Algorithm

Metrics

4
Cited By
0.59
FWCI (Field Weighted Citation Impact)
14
Refs
0.74
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Visual Attention and Saliency Detection
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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