基于局部对比度的视觉注意模型的比较与研究
毕业论文关键词：视觉注意，感兴趣区域，目标检测，局部对比
Compare and Research of Visual Attention Models based on Local Contrast
Abstract: With the rapid development of the information processing techniques, people want computers to process and analyze the expanding images and videos and to obtain useful information from large amounts of data fast and easily. The visual attention model detects regions of interest by detecting prominent points in an image, for it takes regions of interest, which contain potential target as the muster of points that have prominent features．In image processing tasks such as image retrieval, target detection and surveillance, it would be more convenient to focus on regions of interest detected by visual attention model than focus on the whole image. The texture coherence feature is added into the detection of primary visual features as a kind of the primary visual feature in the new model, which makes use of intensity, color, orientation and coherence information to form conspicuity maps. The conspicuity maps are combined as saliency map by a global enhancement method to guide attention and detect regions of interest.
Keywords: visual attention, region of interest, target detection, local contrast.
目录
摘要 i
Abstract i
目录 iii
1 绪论 1
1.1 课题的目的和意义 1
1.2 国内外研究现状与水平 2
1.3 总结： 5
2 相关技术的介绍和分析 6
2.1 IT方法 6
2.2 GB方法 8
2.3 AC方法 9
2.4 CA方法 10
2.5 小结 12
3 系统设计 13
3.1 软件介绍 13
3.2 主界面设计 13
3.3 AC算法界面设计 14
3.4 GB算法界面设计 17
3.5 CA算法界面设计 17
3.6 IT算法界面设计 18
3.7 性能比较 19
致谢 22
参考文献 23
1 绪论
1.1 课题的目的和意义
随着互联网和信息技术的迅猛发展，图像已经成为人们获取和传播信息最主要的载体之一，人们通过互联网等多种途径可以轻松地获取到各个方面的图像信息。为了从众多的图像数据中找到真正感兴趣或对自己有用的信息，人们希望利用计算机完成对图像内容的分析、检索、识别等繁重的视觉任务。这些需求对图像处理与模式识别的理论方法和技术提出了更高的要求和挑战。图像处理是利用计算机对图像进行分析、加工和处理，使其满足视觉、心理以及其他要求的方法和技术，通过借助模式识别手段，最终实现对图像内容的理解。在过去二十多年间，相关领域的研究取得了很大进展。但是，随着数字媒体（图像和视频）数据的日益膨胀，传统的方法和技术已经不能使最先进的计算机系统完全具备处理和分析这些海量数据的能力。