A Method for the Estimation of the Square Size in the Chessboard Image using Gray-level Co-occurrence Matrix

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A Method for the Estimation of the Square Size in the Chessboard Image using Gray-level Co-occurrence Matrix

The paper proposes a new simple procedure for measuring the square size employing the gray-level co-occurrence matrix of a chessboard image. As the size of the square structure in a chessboard image provides the geometric constraint information among the corners, it is available to improve the precision of extracting corners and serve the camera calibration. The co-occurrence matrix of a chessboard image is constructed to obtain the statistic information of the grayscale distribution. The 2D offset of the matrix is parameterized to calculate the correlation which is regarded as the implication of the repetition probability of the similar textures. A descending tendency is observed in the experiments because the similarity decreases with the greater offset. However, minimum and maximum are captured in the correlation curve, which represents that the square texture reappears with the periods of one and two square size, separately. The size of the square is tested by applying the first minimum of the correlation. The experiments are performed on the horizontal and vertical directions which are corresponding to the length and the width of the square, respectively. The experiments prove that the described method has the potential to measure square size of the chessboard.

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Measurement Science Review

The Journal of Institute of Measurement Science of Slovak Academy of Sciences

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IMPACT FACTOR 2017: 1.345
5-year IMPACT FACTOR: 1.253



CiteScore 2017: 1.61

SCImago Journal Rank (SJR) 2017: 0.441
Source Normalized Impact per Paper (SNIP) 2017: 0.936

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