摘要
目的为了提高轮廓检测的综合性能,特别是增强弱轮廓边缘的提取能力,在结合视觉机制的基础上提出了本文方法。方法模拟视觉信息在视通路中的传递和处理过程,首先根据神经节细胞的中心周边拮抗机制,实现初级轮廓信息的快速提取;接着利用高斯函数与高斯差函数之间的差异性来模拟外膝体非经典感受野的调制作用,实现纹理背景的抑制;然后构建了一种V1区多朝向简单细胞感受野模型,提出了一种基于负值效应的DOG(difference of Gaussians)响应改进评价模式;最后考虑V1区复杂细胞在表征视觉高级特征的能力,给出了一种基于并行处理的视通路视觉响应融合模型,实现目标轮廓的检测与增强。结果为了验证本文方法对自然场景图像的轮廓检测具备有效性,本文选取RuG轮廓检测数据库中的40幅自然场景图进行轮廓检测实验,并与二维高斯导函数模型(DG)、组合感受野模型(CORF)和空间稀疏约束纹理抑制模型(SSC)等3种典型的自然图像轮廓检测方法进行了分析比较。结果表明,本文方法检测提取到的主体轮廓更加完整,具有较高的图像纯净度,整体上反映了本文所提轮廓检测方法所具备的生物智能性。本文方法的平均P指标为0.45,相较于对比方法具有更好的轮廓检测性能。结论本文方法具有较好的自然轮廓检测提取能力,尤其对于图像包含部分弱轮廓边缘的检测。本文构建的新模型将有助于对视通路中各层级功能和内在机制的理解,也将为基于视觉机制的图像分析和理解提供一种新的思路。
Objective Visual information is the main source of human perception of outside information. The visual system of the human brain, as the most important means of obtaining information from the outside world, has a near-perfect information processing capability, which is far superior to existing computer vision systems in all aspects. The model description of the visual information processing mechanism can provide a novel way of solving engineering application problems, such as image analysis and understanding. Therefore, the study of the visual information processing mechanism has become an important direction in brain and cognitive science research. The complexity of the visual system lies in the complexity of information transmission between neurons; multiple information paths exist, and high cortical information demonstrates feedback regulation. Visual computing is an important means of studying visual information processing mechanisms and promoting the development of computer vision-related applications. Researchers can study the coding and processing of visual information from different ranges, such as microcosmic to macroscopic and molecular to behavioral, with the continuous improvement of the technical means of visual mechanism research. However, only the experimental data, which are organized organically from different levels and angles, can help determine the laws and mechanisms of nature. Contour detection is crucial to understanding the function and application of a high cortex visual perception. Method This study considers the process of visual information transmission by taking the entire visual paths as the object in studying the visual response characteristics of different mechanisms in the paths and constructing the visual fusion model of multiple visual pathways. The response model of the antagonistic mechanism of ganglion cells in the pathway is improved, the negative value of the primary contour response is preserved, and several features of the non-classical receptive field of the lateral geni
出处
《中国图象图形学报》
CSCD
北大核心
2018年第2期182-193,共12页
Journal of Image and Graphics
基金
国家自然科学基金项目(61501154)~~
关键词
轮廓检测
多感受野
DOG负值效应
多视通路
视觉机制
contour detection
multiple receptive fields
negative value effect of DOG
multiple visual pathways
visualmechanism
