Model-Based GA Evolutionary 3-D Position Measurement Method
Model-Based GA Evolutionary 3-D Position Measurement Method
复制标题
基于模型的遗传算法进化3维位置测量方法
DOI：
10.4028/www.scientific.net/amm.226-228.1866
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Xiao Li
中科院分区：
文献类型：
--
作者：
X. Liu;Wei Song;Yanan Zhang;Xiao Li
本文提出了一种与视觉相关的三维位置测量技术。该方法利用遗传算法（GA）和未处理的灰度图像输入的视觉，以执行识别的目标被成像与已知的目标对象形状。将目标形状识别和位置检测问题转化为基于模型的评价函数的优化问题，即基于表面条带模型的适应度函数，该函数计算内表面和轮廓条带之间的亮度差。为了评估所提出的3-D识别方法，实验由未经处理的灰度图像已输入识别图像中的球。实验结果表明了该方法在三维位置检测中的有效性。
This paper presents a vision-related technique for 3-D position measurement. The proposed method utilizes the genetic algorithm (GA) and unprocessed grayscale image input from vision, in order to perform recognition of a target being imaged with known target object shape. The problem to recognize the target shape and simultaneous detection of the position, is converted to an optimistic problem of a model-based evaluation function, named as surface-strips model-based fitness function that consists in the computation of the brightness difference between an internal surface and a contour-strips. In order to evaluate the proposed 3-D recognition method, experiments by an unprocessed grayscale image have been input to recognize a ball in the image. The results show the effectiveness of this method for 3-D position detection.