Open AccessStatistical behavior analysis and precision optimization for the laser stripe center detector based on Steger's algorithm
Author(s) -
Qi Li,
Yixin Zhang,
Xuping Zhang,
Shun Wang,
Fei Xie
Publication year - 2013
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.21.013442
Subject(s) - optics , laser , computer science , robustness (evolution) , artificial intelligence , gaussian , gaussian blur , smoothing , detector , kernel (algebra) , speckle pattern , computer vision , image processing , mathematics , image (mathematics) , physics , image restoration , biochemistry , chemistry , quantum mechanics , combinatorics , gene
Triangulation laser range scanning, which has been wildly used in various applications, can reconstruct the 3D geometric of the object with high precision by processing the image of laser stripe. The unbiased line extractor proposed by Steger is one of the most commonly used algorithms in laser stripe center extraction for its precision and robustness. Therefore, it is of great significance to assess the statistical performance of the Steger method when it is applied on laser stripe with Gaussian intensity profile. In this paper, a statistical behavior analysis for the laser stripe center extractor based on Steger method has been carried out. Relationships between center extraction precision, image quality and stripe characteristics have been examined analytically. Optimal scale of Gaussian smoothing kernel can be determined for each laser stripe image to achieve the highest precision according to the derived formula. Flexible three-step noise estimation procedure has been proposed to evaluate the center extraction precision of a typical triangulation laser scanning system by simply referring to the acquired images. The validity of our analysis has been verified by experiments on both artificial and natural images.