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Proceedings Paper

Research on real-time object labeling methods
Author(s): Zhongbi Chen; Jingju Cai; Qiheng Zhang; Zhiyong Xu
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Paper Abstract

Real-time multi-objects labeling, which includes segmenting target, picking up features and labeling object automatically, is a study field of Automatic Target Recognition (ATR). Labeling object in an image is a very important step in many application areas such as target scouting and tracking, circuit board and IC mask inspection, environmental and medical image analysis. In this paper, the approaches on object description are classified. Based on the comparison of different methods in many aspects, some representative methods on object labeling, including their basic principles, characteristics, and drawbacks are researched. At the same time, one optimized technique, fast object description on multi-objects labeling, is presented. This fast object labeling algorithm is based on the pixel labeling method. Using the neighboring relationship of binary pixel points in the contiguous scanning lines, this fast approach can complete the pick-up of object labels and the combination of equal target labels during scanning once. Finally, in this approach, the labeling of objects and pick-up of features are accomplished. Experimental results show that the improved algorithm can be used to segment object and label multi-targets, and the performance of the algorithm is fast-speed, practical and simple as well as with the high ability of processing complex patterns.

Paper Details

Date Published: 30 December 2008
PDF: 10 pages
Proc. SPIE 7268, Smart Structures, Devices, and Systems IV, 726817 (30 December 2008); doi: 10.1117/12.806514
Show Author Affiliations
Zhongbi Chen, Institute of Optics and Electronics (China)
Jingju Cai, Institute of Optics and Electronics (China)
Qiheng Zhang, Institute of Optics and Electronics (China)
Zhiyong Xu, Institute of Optics and Electronics (China)


Published in SPIE Proceedings Vol. 7268:
Smart Structures, Devices, and Systems IV
Said Fares Al-Sarawi; Vijay K. Varadan; Neil Weste; Kourosh Kalantar-Zadeh, Editor(s)

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