Robust shape-preserving contour tracing with synchronous redundancy pruning

Abstract

This paper presents a concise, robust shape-preserving contour tracing scheme for efficiently extracting a highly representative one-pixel-width closed contour for the profiles of heterogeneous objects from digitally processed images regardless of noise existence. The tracing mechanism comprises two synchronous-running modules, namely a progressive boundary linking (PBL) module and a synchronous redundancy pruning (SRP) module. PBL applies concise pixel-based decision-making criteria to select and links suitable pixels belonging to the object’s contour in real-time. At the same time, SRP simultaneously removes random noises and prunes perceptually trivial branches/cracks, which are regarded as commonly-acknowledged redundancies, from the constructing contour curve. Thus, the relatively meaningful details of original object profile can be preserved on the extracted contour. The performances of proposed contour tracing method in extracting object contours from clean and noisy images are both qualitatively and quantitatively compared with that of a conventional digital signal processing (DSP) technique and mathematical morphology boundary extraction method, and integration of the mathematical morphology noise-cleaning process and conventional DSP technique, respectively. Overall, the simulation results indicate that the one-pixel-width closed contours extracted by the proposed mechanism have a greater degree of precision and noise suppression than those extracted by the conventional DSP method, the mathematical morphology boundary extraction method, and conventional DSP method following morphological cleaning process. Therefore, the proposed contour tracing mechanism could offer a viable efficient contour-extraction tool in supporting some well-known image processing applications such as object shape-coding, pattern-recognition and posture change detection, and so forth.