面向ISAC系统的二维目标识别

M.P. Jarreau, H.G. Senel, A. Kara, K. Kawamura
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引用次数: 4

摘要

智能软臂控制(ISAC)系统是一种语音激活的肢体残疾机器人辅助系统,涉及到对物体识别的要求。作者简要介绍了ISAC系统,并描述了在二维目标识别和定向方面的工作。目标识别的研究涉及到从数字化图像中提取相关信息。采用非递归分割算法对二值图像进行分割,分离出目标。接下来,为分割例程找到的每个对象生成两个直方图:一个关于物体质心的距离直方图和一个方向直方图。用距离直方图识别目标,用方向直方图寻找目标的方向。此外,还介绍了一种非递归分割算法、一种基于直方图的识别和方向检测算法以及一种基于多变量判别分析的识别算法
本文章由计算机程序翻译,如有差异,请以英文原文为准。
2-dimensional object recognition for the ISAC system
The intelligent soft arm control (ISAC) system is a voice-activated robotic aid for the physically disabled which involves the requirement for object recognition. The authors present a brief description of the ISAC system and describe work in 2-D object recognition and orientation. The research in object recognition involves the extraction of relevant information from digitized images. A binary image was processed by a nonrecursive segmentation algorithm to isolate each object. Next, two histograms were generated for each object found by the segmentation routine: a distance histogram about the object's center of mass and an orientation histogram. The distance histogram was used for identification of objects and the orientation histogram was used for finding their orientation. Additionally, a nonrecursive segmentation algorithm, a histogram-based recognition and orientation detection algorithm and a multivariate-discriminant-analysis-based recognition algorithm are described.<>
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