彩色伪随机编码图像特征点神经网络匹配

doi:10.3969/j.issn.1000-1158.2016.05.09

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Abstract In order to study the theory of uncalibrated 3D euclidean reconstruction based on single image. An effective active- machine technique with structured light illumination is introduced which applies pseudo-random color code. Each interest point on scene surface can be identified exclusively according to the window property of pseudo-random array. It is found out that this active machine system can solve the correspondence between images in the passive machine system. Image recognition using neural networks can easily solve characteristic point match problem in coding structured light active vision system, the experiment is satisfactory.

Key words： metrology image recognition active machine system pseudo-random neural network correspondence between the camera images euclidean reconstruction uncalibration

Received: 27 October 2014 Published: 29 July 2016

PACS:

TB96

Corresponding Authors: Su-yin LIAO E-mail: 664242473@qq.com

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	Articles by authors
	LIAO Su-yin
	WU Bo
	WEI Min
	ZHAO Yan
	LI Gui-hua
	ZHANG Mei

Cite this article:

LIAO Su-yin,WU Bo,WEI Min, et al. Pseudo Random Color Encoded Image Feature Points Matching Based on Neural Network[J]. Acta Metrologica Sinica, 2016, 37(5): 494-498.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2016.05.09 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2016/V37/I5/494

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