基于Gestalt视觉心理学和最小F-范数的图像显著区域检测和分割
根据Gestalt视觉心理学说，提出了一种新的图像显著区域检测方法。通过不同程度降低双对立颜色或亮度的特征图像对比度来抑制图像中次要特征对应的区域，增强主要特征对应的显著性区域；通过矩阵的最小F-范数确定符合Gestah视觉心理学的特征图像的合成方案，并利用Gestalt视觉心理学的核心理论来检验和自适应修改组合方案，得到最佳的显著图；利用Otsu法对显著图像进行二值化操作来完成图像的分割。实验结果表明，算法可以从复杂的自然彩色图像申较为完整地提取并分割显著目标，实验结果与MSRA数据库手工分割结果相一致，在满足实时性需求的基础上能比传统方法更加准确、完整地提取图像的显著性区域。...
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| Published in | 计算机应用研究 Vol. 34; no. 11; pp. 3504 - 3509 |
|---|---|
| Main Author | |
| Format | Journal Article |
| Language | Chinese |
| Published |
延边大学工学院计算机科学与技术学科,吉林延吉133002
2017
延边大学智能信息处理研究室,吉林延吉133002 |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1001-3695 |
| DOI | 10.3969/j.issn.1001-3695.2017.11.068 |
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| Abstract | 根据Gestalt视觉心理学说，提出了一种新的图像显著区域检测方法。通过不同程度降低双对立颜色或亮度的特征图像对比度来抑制图像中次要特征对应的区域，增强主要特征对应的显著性区域；通过矩阵的最小F-范数确定符合Gestah视觉心理学的特征图像的合成方案，并利用Gestalt视觉心理学的核心理论来检验和自适应修改组合方案，得到最佳的显著图；利用Otsu法对显著图像进行二值化操作来完成图像的分割。实验结果表明，算法可以从复杂的自然彩色图像申较为完整地提取并分割显著目标，实验结果与MSRA数据库手工分割结果相一致，在满足实时性需求的基础上能比传统方法更加准确、完整地提取图像的显著性区域。 |
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| AbstractList | 根据Gestalt视觉心理学说，提出了一种新的图像显著区域检测方法。通过不同程度降低双对立颜色或亮度的特征图像对比度来抑制图像中次要特征对应的区域，增强主要特征对应的显著性区域；通过矩阵的最小F-范数确定符合Gestah视觉心理学的特征图像的合成方案，并利用Gestalt视觉心理学的核心理论来检验和自适应修改组合方案，得到最佳的显著图；利用Otsu法对显著图像进行二值化操作来完成图像的分割。实验结果表明，算法可以从复杂的自然彩色图像申较为完整地提取并分割显著目标，实验结果与MSRA数据库手工分割结果相一致，在满足实时性需求的基础上能比传统方法更加准确、完整地提取图像的显著性区域。 TP391.41; 根据Gestalt视觉心理学说,提出了一种新的图像显著区域检测方法.通过不同程度降低双对立颜色或亮度的特征图像对比度来抑制图像中次要特征对应的区域,增强主要特征对应的显著性区域;通过矩阵的最小F-范数确定符合Gestalt视觉心理学的特征图像的合成方案,并利用Gestalt视觉心理学的核心理论来检验和自适应修改组合方案,得到最佳的显著图;利用Otsu法对显著图像进行二值化操作来完成图像的分割.实验结果表明,算法可以从复杂的自然彩色图像中较为完整地提取并分割显著目标,实验结果与MSRA数据库手工分割结果相一致,在满足实时性需求的基础上能比传统方法更加准确、完整地提取图像的显著性区域. |
| Abstract_FL | According to Gestalt visual psychology,this paper developed a new image saliency detection method.Firstly,by reducing the contrast of dual opponent colors feature image and luminance feature image,the method suppressed secondary feature of the image and heightened the salient region.Secondly,by minimum F-norm,it determined the combination scheme of feature image according with Gestalt visual psychology.Then,using core theories of Gestalt visual psychology,it examined and adaptively adjusted the combination scheme to get best saliency map.Finally,this method used Otsu method to binary the saliency image and completed salient region segmentation.Simulation experiments show that this method can completely extract salient object in real time from complex natural-color image.Salient region segmentation results are in line with ground-truth data of MSRA database.Compared to traditional methods,integrity and accuracy of segmentation results are more accurate and more complete. |
| Author | 方志明 崔荣一 金璟璇 |
| AuthorAffiliation | 延边大学工学院计算机科学与技术学科,吉林延吉133002 延边大学智能信息处理研究室,吉林延吉133002 |
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| Author_FL | Cui Rongyi Jin Jingxuan Fang Zhiming |
| Author_FL_xml | – sequence: 1 fullname: Fang Zhiming – sequence: 2 fullname: Cui Rongyi – sequence: 3 fullname: Jin Jingxuan |
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| ClassificationCodes | TP391.41 |
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| Copyright | Copyright © Wanfang Data Co. Ltd. All Rights Reserved. |
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| DocumentTitleAlternate | Image salient region detection and segmentation based on Gestalt visual psychology and minimum F-norm |
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| Keywords | Gestalt视觉心理学 feature image 特征图像 图像显著性区域 minimum F-norm Gestalt visual psychology 最小F-范数 image salient region |
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| Notes | 51-1196/TP image salient region; Gestalt visual psychology; teature image; minimum F-norm According to Gestalt visual psychology, this paper developed a new image saliency detection method. Firstly, by reducing the contrast of dual opponent colors feature image and luminance feature image, the method suppressed seeondal7 featroy of the image and heightened the salient region. Secondly, by minimum F-norm, it determined the combination scheme of feature image according with Gestalt visual psychology. Then, using core theories of Gestalt visual psychology, it examined and adaptively adjusted the combination scheme to get best saliency map. Finally, this method used Otsu method to binary the saliency image and completed salient region segmentation. Simulation experiments show that this method can completely extract salient object in real lime from complex natural-color image. Salient region segmentation results are in line with ground-trnth data of MSRA database. Compared to traditional methods, integrity and accur |
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| Publisher | 延边大学工学院计算机科学与技术学科,吉林延吉133002 延边大学智能信息处理研究室,吉林延吉133002 |
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| SubjectTerms | Gestalt视觉心理学 图像显著性区域 最小F-范数 特征图像 |
| Title | 基于Gestalt视觉心理学和最小F-范数的图像显著区域检测和分割 |
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