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Automatic positioning and detection method for jewelry based on principal component analysis
JIA Yulan, HUO Zhanqiang, HOU Zhanwei, WANG Zhiheng
Journal of Computer Applications    2016, 36 (10): 2922-2926.   DOI: 10.11772/j.issn.1001-9081.2016.10.2922
Abstract421)      PDF (739KB)(427)       Save
Concerning the problem that it is difficult to estimate the shape characteristics of irregular objects, a new automatic detection method for irregular jewelry images was put forward by introducing the concept of Principal Component Analysis (PCA) to realize the automatic measurement for jewelry. First, the principal axis of target image was extracted by PCA. Then, four vertices of the external rectangle of jewelry were computed according to the optimization direction of the principal axis. Last, the best-fitted rectangle of irregular contour was positioned to detect the irregular shape of the jewelry. The proposed method was applied to real jewelry images, experimental results illustrate that this algorithm can accurately locate the target in the image. Compared with the linear spectral frequency method and the projection rotation translation method, the subjective and objective evaluation results prove the superiority of the proposed algorithm.
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