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| Automatic Extraction Method for Texture Periodicity Based on Improved Normalized Distance Matching Function |
| JIANG Sheng1,2, TANG Guo-An1, TAO Yang1,2 |
1.Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 2100462.
2.Provincial Fundamental Geomatics Center of Jiangsu, Nanjing 210013 |
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Abstract Based on improved normalized distance matching function (INDMF), an automatic extraction method for regular and near-regular structural texture periodicity is proposed. Firstly, the dissimilarity of gray level co-occurrence matrices is calculated as the texture characteristic, and the INDMF edge is removed. Thus, the values between different peak intervals are more stable. Secondly, an adaptive and anti-noise peak searching approach is adopted to find initial periodic sequence and extract texture periodicity. Next, with the consideration of the characteristics of artificial and natural texture, the final periodicity is calculated by sequence mode. The results of extraction experiments on Brodatz and PSU datasets show the effectiveness and the efficiency of the proposed method. Moreover, the proposed method is more stable and accurate than the method of forward difference of accumulative DMF for impulsive salt and pepper noisy images and projective deformed images.
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Received: 03 June 2013
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2014, Vol. 27 
