摘要
自然场景自动检测目标轮廓是非常困难的。该文提出了一种基于复合感受野的图像轮廓检测仿生模型。在传统的基于抑制模型的基础上引入去抑制机制,在减少背景纹理干扰的同时,保护较弱的轮廓,从而尽量保持轮廓的完整性。实验结果表明,这种仿生模型可以有效地抑制纹理边缘,减少对轮廓的破坏,提高了自然背景中轮廓检测的性能。
Contour detection from natural scenes is a tough task in computer vision. This paper proposes a visual model of contour detection based on compound receptive field. By inducing dis-inhibition mechanism to traditional model that was based on inhibition mechanism, inferences are suppressed while weak edges are preserved, so that the integrity of contour is improved. Experiment results show that this approach can suppress edges due to texture, protect object contour and improve the performance of contour detection from nature scene.
出处
《电子与信息学报》
EI
CSCD
北大核心
2009年第7期1630-1634,共5页
Journal of Electronics & Information Technology
基金
国家973计划项目(2007CB311005)
国家863计划项目(2006AA01Z129)
福建省自然科学基金(A0710020)
厦门大学985二期信息创新平台项目资助课题
关键词
目标识别
轮廓检测
初级视皮层
复合感受野
Target identification
Contour detection
Primary visual cortex
Compound Receptive Field(CRF)