Edge and line oriented contour detection: State of the art

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We present an overview of various edge and line oriented approaches to contour detection that have been proposed in the last two decades. By edge and line oriented we mean methods that do not rely on segmentation. Distinction is made between edges and contours. Contour detectors are divided in local and global operators. The former are mainly based on differential analysis, statistical approaches, phase congruency, rank order filters, and combinations thereof. The latter include computation of contour saliency, perceptual grouping, relaxation labeling and active contours. Important aspects are covered, such as preprocessing aimed to suppress texture and noise, multiresolution techniques, connections between computational models and properties of the human visual system, and use of shape priors. An overview of procedures and metrics for quantitative performance evaluation is also presented. Our main conclusion is that contour detection has reached high degree of sophistication, taking into account multimodal contour definition (by luminance, color or texture changes), mechanisms for reducing the contour masking influence of noise and texture, perceptual grouping, multiscale aspects and high-level vision information.

论文关键词:Contour detection,Preprocessing,Local pattern analysis,Contour salience,Gestalt grouping,Closure,Scale–space,Performance evaluation

论文评审过程:Received 12 March 2009, Revised 21 July 2010, Accepted 18 August 2010, Available online 27 August 2010.

论文官网地址:https://doi.org/10.1016/j.imavis.2010.08.009