Ms. Jun Cheng Profile

Jun Cheng

at Huazhong University of Science and Technology

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Proceedings Article | 14 December 2015 Paper

LiveWire interactive boundary extraction algorithm based on Haar wavelet transform and control point set direction search

Jun Cheng, Jun Zhang, Jinwen Tian

Proceedings Volume 9812, 98120E (2015) https://doi.org/10.1117/12.2204776

KEYWORDS: Feature extraction, Image processing algorithms and systems, Wavelet transforms, Image resolution, Image segmentation, Reconstruction algorithms, Detection and tracking algorithms, Wavelets, Image processing, Computer programming

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Based on deep analysis of the LiveWire interactive boundary extraction algorithm, a new algorithm focusing on improving the speed of LiveWire algorithm is proposed in this paper. Firstly, the Haar wavelet transform is carried on the input image, and the boundary is extracted on the low resolution image obtained by the wavelet transform of the input image. Secondly, calculating LiveWire shortest path is based on the control point set direction search by utilizing the spatial relationship between the two control points users provide in real time. Thirdly, the search order of the adjacent points of the starting node is set in advance. An ordinary queue instead of a priority queue is taken as the storage pool of the points when optimizing their shortest path value, thus reducing the complexity of the algorithm from O[n²] to O[n]. Finally, A region iterative backward projection method based on neighborhood pixel polling has been used to convert dual-pixel boundary of the reconstructed image to single-pixel boundary after Haar wavelet inverse transform. The algorithm proposed in this paper combines the advantage of the Haar wavelet transform and the advantage of the optimal path searching method based on control point set direction search. The former has fast speed of image decomposition and reconstruction and is more consistent with the texture features of the image and the latter can reduce the time complexity of the original algorithm. So that the algorithm can improve the speed in interactive boundary extraction as well as reflect the boundary information of the image more comprehensively. All methods mentioned above have a big role in improving the execution efficiency and the robustness of the algorithm.

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