结合双视通路与尺度信息融合的轮廓检测方法  

A contour detection method combing dual visual pathway and scale information fusion

作　　者：杜仕荣 范影乐 蔡哲飞 房涛 Du Shirong;Fan Yingle;Cai Zhefei;Fang Tao(Laboratory of Pattern Recognition and Image Processing,Hangzhou Dianzi University,Hangzhou 310018,China;College of Electronics and Information,Hangzhou Dianzi University,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学模式识别与图像处理实验室,杭州310018 [2]杭州电子科技大学电子信息学院,杭州310018

出　　处：《中国图象图形学报》2024年第12期3657-3669,共13页Journal of Image and Graphics

基　　金：浙江大学计算机辅助设计与图形系统全国重点实验室开放课题项目(A2330)。

摘　　要：目的考虑到图像信息在视觉通路中的表征是多尺度的,为了实现自然场景下多对比度分布图像的轮廓检测任务,提出了一种基于双视通路尺度信息融合的轮廓检测新方法。方法首先构建对亮度信息敏感和对颜色信息敏感的大细胞(M)、小细胞(P)并行通路,构建不同尺度的感受野模拟神经节细胞对刺激的模糊和精细感知,使用亮度对比度和色差信息指导不同尺度感受野响应的自适应融合,使其能够充分提取亮度轮廓和颜色轮廓。其次结合外膝体(lateral geniculate nucleus,LGN)多尺度方向差异编码与多尺度朝向选择性抑制方法,构建显著轮廓提取模型,实现轮廓区域的增强以及背景纹理的抑制。最后将加工后的亮度轮廓和颜色轮廓前馈至初级视皮层(V1)区,构建双通道响应权重调节模型整合M、P通路所得信息,进一步丰富轮廓。结果本文使用BSDS500(berkeley segmentation data set)图像库和NYUD(New York University-depth)图像库对提出的算法进行验证,其中在BSDS500图像库的最优平均准确率(average precision,AP)指标为0.74,相对于SCSI(subfield-based center-surround inhibition)、BAR(bilateral asymmetric receptive)和SED(surround-modulated edge detection)等基于生物视觉机制的检测方法有4%~13%的提升,所得结果轮廓图也更为连续、准确。结论本文利用M、P双通路机制以及亮度信息和颜色信息在前端视觉通路中的编码过程实现轮廓信息的加工与提取,可以有效实现自然图像的轮廓检测,尤其是对于图像中的细微轮廓边缘的检测,也为研究更高级皮层中视觉信息机制提供新的思路。Objective The extraction and utilization of contour information,as a low-level visual feature of the target subject,contribute to the efficient execution of advanced visual tasks,such as object detection and image segmentation.When processing complex images,contour detection based on biological vision mechanisms can quickly extract object contour information.However,the perception of primary contour information is currently based on a single scale receptive field template or a simple fusion of multiple scale receptive field templates,which ignores the dynamic characteristics of receptive field scales and makes it difficult to accurately extract contours in complex scenes.Considering the serial parallel transmission and integration mechanism of visual information in the magnocellular(M)and parvocellular(P)dual vision pathways,we propose a new contour detection method based on the fusion of dual vision pathway scale information.Method First,we introduce Lab,a color system that is close to human visual physiological characteristics,to extract color difference and brightness information from an image.Compared with conventional RGB color systems,Lab is more in line with the way the human eye perceives visual information.Considering that the scale of the receptive field of ganglion cells varies with the size of local stimuli to adapt to different visual task requirements across various scenes,a smaller scale of the receptive field corresponds to a more refined perception of detailed information.We then simulate the fuzzy and fine perception of the stimuli by ganglion cells using two different scale receptive fields,and we use color difference and brightness contrast information to guide the adaptive fusion of large-and small-scale receptive field responses and highlight the contour details.Second,considering the differences in the perception of orientation information among receptive fields at different scales of the lateral geniculate body,we introduce the standard deviation of the optimal orientation obtained from pe

关 键 词：轮廓检测 双视通路 多尺度 自适应融合 方向差异 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]