基于8邻域模式匹配技术的二维形状轮廓识别与检索

Muzameel Ahmed, V. Aradhya
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引用次数: 0

摘要

提出了一种二维形状识别与检索技术。所提出的技术是基于表示形状轮廓上的每个点或像素的8邻域模式。这些图案被用作与物体形状相匹配的框架。通过遍历形状轮廓进行识别和检索,并考虑8邻域模式对轮廓上的每个点进行分析。在等高线遍历过程中,8邻域模式被分配了唯一的标签。通过比较待匹配形状的轮廓遍历所获得的命中值来评估形状之间最佳匹配的代价。分别采用留一策略和标准靶心评分进行识别和检索。在MPEG-7数据集和鸡块数据集上进行了实验。结果表明,该方法在识别和检索方面都优于大多数先前提出的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
2D Shape Recognition and Retrieval Using Shape Contour Based on the 8-Neighborhood Patterns Matching Technique
A technique for 2D shape recognition and retrieval is proposed. The proposed technique is based on the 8-neighborhood pattern which represents each point or pixel on the contour of the shape. These patterns are used as a framework in matching the shape of the object. The recognition and retrieval process are conducted by traversing through the contour of the shape and analyzes each point on the contour by considering the 8-neighborhood pattern. The 8-neighborhood patterns are assigned unique labels which are computed on their every occurrence during contour traversal. The cost of the best match between the shapes is evaluated by comparing the hit value obtained by the contour traversal of the shapes to be matched. The recognition and retrieval are carried out using the leave-one-out strategy and standard bull eye score, respectively. The proposed method is experimented on the MPEG-7 data set and the chicken piece data set. The results both for recognition and retrieval outperform most of the previously proposed methods.
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