Based On Edge Extraction of ASM Automatic Landmark Placement
In the Active Shape Model, the most time consuming and
scientifically unsatisfactory part of building shape models is the
labeling of the training images. Manually placing hundreds (in
2D) of points on every image is both tedious and error prone. To
reduce the burden, the combination of the image edge
information and the traditional manual calibration methods have
been developed. This method improves the calibration accuracy,
and obtains more accurate statistical shape model and local
texture model. Aiming at the characteristics of ASM modeling,
this paper adopts a multiscale wavelet transform modulus
maximum method of edge extraction, using the maximum
variance method to obtain a threshold, after the use of
connectivity judgment for each scale edge fusion. The simulation
results show that, this algorithm can effectively reduce the
burden, improve the modeling accuracy.
Keywords: ASM, multiscale, wavelet modulus maxima, maximum between-cluster variance
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ABOUT THE AUTHORS
Zhang Liguo
Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China
Li Xiaolin
Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China
Li Huijuan
Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China
Zhang Liguo
Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China
Li Xiaolin
Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China
Li Huijuan
Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China
