A real-time semi-automatic video segmentation system based on mathematical morphology

Chia-Hao Chang; Chi-Hao Wu; Jun-Cheng Chen; Jin-Hau Kuo; Ja-Ling Wu

doi:10.1117/12.633441

24 June 2005 A real-time semi-automatic video segmentation system based on mathematical morphology

Chia-Hao Chang, Chi-Hao Wu, Jun-Cheng Chen, Jin-Hau Kuo, Ja-Ling Wu

Proceedings Volume 5960, Visual Communications and Image Processing 2005; 59606A (2005) https://doi.org/10.1117/12.633441
Event: Visual Communications and Image Processing 2005, 2005, Beijing, China

Abstract

Mathematic morphology provides a systematic approach to analyze the geometric characteristics of signals or images, and has been widely applied to many applications such as edge detection, object segmentation, noise suppression. In this paper, a supervised morphology based video segmentation system is proposed. To find where a semantic object resides, the user could click the mouse near the boundary of the object in the first frame of a video to indicate its rough definition, shape and location. The proposed system will automatically segment the first frame by first locating the searching area and then classifying the units in it into object part and non-object part to find out the continuous contour by means of a multi-valued watershed algorithm using a hierarchical queue. An adaptive morphological operator based on edge strength, which is computed by a multi-scale morphological gradient algorithm, is proposed to lower the error of user assistance such that the searching area is created correctly. Once extended to video object segmentation, a fast video tracking technique is applied. Under the assumption of small motion, the object can be segmented in real-time. Moreover, an accuracy evaluation mechanism is proposed to ensure the robustness of the segmentation.

Citation Download Citation

Chia-Hao Chang, Chi-Hao Wu, Jun-Cheng Chen, Jin-Hau Kuo, and Ja-Ling Wu "A real-time semi-automatic video segmentation system based on mathematical morphology", Proc. SPIE 5960, Visual Communications and Image Processing 2005, 59606A (24 June 2005); https://doi.org/10.1117/12.633441

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