Machine Vision|9 Article(s)
Two-dimensional vision measurement approach based on local sub-plane mapping
Fuqiang Zhou, Xinghua Chai, Tao Ye, and Xin Chen
Chinese Optics Letters
  • Publication Date: Dec. 10, 2015
  • Vol. 13, Issue 12, 121501 (2015)
Color restoration method of printing in machine visual detection
Peng Liu, Ning Zhao, Linghui Ren, and Qianqian Xu
Chinese Optics Letters
  • Publication Date: Mar. 04, 2014
  • Vol. 12, Issue s1, S11501 (2014)
Robust iris biometric system for visible wavelength data
Farmanullah Jan, Imran Usman, and Shahid A.
Commercial iris biometric systems exhibit good performance for near-infrared (NIR) images but poor performance for visible wavelength (VW) data. To address this problem, we propose an iris biometric system for VW data. The system includes localizing iris boundaries that use bimodal thresholding, Euclidean distance transform (EDT), and a circular pixel counting scheme (CPCS). Eyelids are localized using a parabolic pixel counting scheme (PPCS), and eyelashes, light reflections, and skin parts are adaptively detected using image intensity. Features are extracted using the log Gabor filter, and finally, matching is performed using Hamming distance (HD). The experimental results on UBIRIS and CASIA show that the proposed technique outperforms contemporary approaches.
Chinese Optics Letters
  • Publication Date: Aug. 02, 2013
  • Vol. 11, Issue 8, 081501 (2013)
Detection of automatic abnormity in the winding and splicing of fiber-optic coil
Haoting Liu, Wei Wang, Xinfeng Li, and Feng Gao
Chinese Optics Letters
  • Publication Date: Sep. 29, 2013
  • Vol. 11, Issue 10, 101501 (2013)
Two-step pose estimation method based on five reference points
Zimiao Zhang, Changku Sun, and Peng Wang
A two-step method for pose estimation based on five co-planar reference points is studied. In the first step, the pose of the object is estimated by a simple analytical solving process. The pixel coordinates of reference points on the image plane are extracted through image processing. Then, using affine invariants of the reference points with certain distances between each other, the coordinates of reference points in the camera coordinate system are solved. In the second step, the results obtained in the first step are used as initial values of an iterative solving process for gathering the exact solution. In such a solution, an unconstrained nonlinear optimization objective function is established through the objective functions produced by the depth estimation and the co-planarity of the five reference points to ensure the accuracy and convergence rate of the non-linear algorithm. The Levenberg-Marquardt optimization method is utilized to refine the initial values. The coordinates of the reference points in the camera coordinate system are obtained and transformed into the pose of the object. Experimental results show that the RMS of the azimuth angle reaches 0.076o in the measurement range of 0o-90o; the root mean square (RMS) of the pitch angle reaches 0.035o in the measurement range of 0o-60o; and the RMS of the roll angle reaches 0.036o in the measurement range of 0o-60o.
Chinese Optics Letters
  • Publication Date: Mar. 28, 2012
  • Vol. 10, Issue 7, 071501 (2012)
Reliable iris localization using integral projection function and 2D-shape properties
Farmanullah Jan, Imran Usman, and Shahrukh Agha
Iris recognition technology recognizes a human based on his/her iris pattern. However, the accuracy of the iris recognition technology depends on accurate iris localization. Localizing a pupil region in the presence of other low-intensity regions, such as hairs, eyebrows, and eyelashes, is a challenging task. This study proposes an iris localization technique that includes a localizing pupillary boundary in a sub-image by using an integral projection function and two-dimensional shape properties (e.g., area, geometry, and circularity). The limbic boundary is localized using gradients and an error distance transform, and the boundary is regularized with active contours. Experimental results obtained from public databases show the superiority of the proposed technique over contemporary methods.
Chinese Optics Letters
  • Publication Date: Sep. 28, 2012
  • Vol. 10, Issue 11, 111501 (2012)
Pose measurement method based on geometrical constraints
Zimiao Zhang, Changku Sun, Pengfei Sun, and Peng Wang
The pose estimation method based on geometric constraints is studied. The coordinates of the five feature points in the camera coordinate system are calculated to obtain the pose of an object on the basis of the geometric constraints formed by the connective lines of the feature points and the coordinates of the feature points on the CCD image plane; during the solution process, the scaling and orthography projection model is used to approximate the perspective projection model. The initial values of the coordinates of the five feature points in the camera coordinate system are obtained to ensure the accuracy and convergence rate of the non-linear algorithm. In accordance with the perspective projection characteristics of the circular feature landmarks, we propose an approach that enables the iterative acquisition of accurate target poses through the correction of the perspective projection coordinates of the circular feature landmark centers. Experimental results show that the translation positioning accuracy reaches ±0.05 mm in the measurement range of 0–40 mm, and the rotation positioning accuracy reaches ±0.06o in the measurement range of 4o–60o.
Chinese Optics Letters
  • Publication Date: Jun. 16, 2011
  • Vol. 9, Issue 8, 081501 (2011)
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