Paper
30 December 2008 Research on real-time object labeling methods
Zhongbi Chen, Jingju Cai, Qiheng Zhang, Zhiyong Xu
Author Affiliations +
Proceedings Volume 7268, Smart Structures, Devices, and Systems IV; 726817 (2008) https://doi.org/10.1117/12.806514
Event: SPIE Smart Materials, Nano- and Micro-Smart Systems, 2008, Melbourne, Australia
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.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhongbi Chen, Jingju Cai, Qiheng Zhang, and Zhiyong Xu "Research on real-time object labeling methods", Proc. SPIE 7268, Smart Structures, Devices, and Systems IV, 726817 (30 December 2008); https://doi.org/10.1117/12.806514
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KEYWORDS
Detection and tracking algorithms

Image segmentation

Binary data

Automatic target recognition

Image processing algorithms and systems

Convolution

Digital signal processing

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