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RISS 인기검색어
- 검색키워드
- 저자 : ( Huynh Trung Manh ) (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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A Saliency Map based on Color Boosting and Maximum Symmetric Surround
Huynh, Trung Manh,Lee, Gueesang THE KOREAN INSTITUTE OF SMART MEDIA 2013 스마트미디어저널 Vol.2 No.2
Nowadays, the saliency region detection has become a popular research topic because of its uses for many applications like object recognition and object segmentation. Some of recent methods apply color distinctiveness based on an analysis of statistics of color image derivatives in order to boosting color saliency can produce the good saliency maps. However, if the salient regions comprise more than half the pixels of the image or the background is complex, it may cause bad results. In this paper, we introduce the method to handle these problems by using maximum symmetric surround. The results show that our method outperforms the previous algorithms. We also show the segmentation results by using Otsu's method.
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Small Object Segmentation Based on Visual Saliency in Natural Images
Manh, Huynh Trung,Lee, Gueesang Korea Information Processing Society 2013 Journal of information processing systems Vol.9 No.4
Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.
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Small Object Segmentation Based on Visual Saliency in Natural Images
( Huynh Trung Manh ),( Gueesang Lee ) 한국정보처리학회 2013 Journal of information processing systems Vol.9 No.4
Object segmentation is a challenging task in image processing and computer vision. In this paper, we present a visual attention based segmentation method to segment small sized interesting objects in natural images. Different from the traditional methods, we first search the region of interest by using our novel saliency-based method, which is mainly based on band-pass filtering, to obtain the appropriate frequency. Secondly, we applied the Gaussian Mixture Model (GMM) to locate the object region. By incorporating the visual attention analysis into object segmentation, our proposed approach is able to narrow the search region for object segmentation, so that the accuracy is increased and the computational complexity is reduced. The experimental results indicate that our proposed approach is efficient for object segmentation in natural images, especially for small objects. Our proposed method significantly outperforms traditional GMM based segmentation.
ScienceON
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