Abstract
In this paper, a new method has been proposed to calculate the differential excitation and orientation components of a texture descriptor, called the Weber local descriptor (WLD), so that not only is the computational complexity of this method reduced, but the orientation component also becomes rotation invariant. Then to classify the color texture images in RGB color space, the proposed modified WLD will be used so that, by extracting WLD features from R, G, and B components of the color space, a one-dimensional histogram is obtained that describes the image. The results of the classification tests performed on four well-known data sets show the effectiveness of the proposed method.
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References
Paci M, Nanni L, Severi S (2013) An ensemble of classifiers based on different texture descriptors for texture classification. J King Saud Univ Sci 25(3):235–244. doi:10.1016/j.jksus.2012.12.001
Zhang J, Tan T (2002) Brief review of invariant texture analysis methods. Pattern Recognit 35(3):735–747. doi:10.1016/S0031-3203(01)00074-7
Costa AF, Humpire-Mamani G, Traina AJM (2012) An efficient algorithm for fractal analysis of textures. In: Graphics, patterns and images (SIBGRAPI), pp 39–46. doi:10.1109/sibgrapi.2012.15
Zhi-Zhong W, Junhai Y (2008) Texture Analysis and Classification With Linear Regression Model Based on Wavelet Transform. Image Processing, IEEE Transactions on 17(8):1421–1430. doi:10.1109/tip.2008.926150
Majid M, Xianghua X, Jasjit S (2009) Handbook of Texture Analysis. Imperial College Press, London
Huang D-S, Zhang X-P, Huang G-B, Zhang Y, He X-J, Han J-H (2005) Texture feature-based image classification using wavelet package transform. In: Advances in intelligent computing. Lecture notes in computer science, vol 3644. Springer, Berlin, pp 165–173. doi:10.1007/11538059_18
Ojala T, Pietikainen M, Maenpaa T (2002) Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. IEEE Trans Pattern Anal Mach Intell 24(7):971–987. doi:10.1109/tpami.2002.1017623
Ojansivu V, Rahtu E, Heikkila J (2008) Rotation invariant local phase quantization for blur insensitive texture analysis. In: 19th international conference on pattern recognition, ICPR, 8–11 Dec. 2008, pp 1–4. doi:10.1109/icpr.2008.4761377
Jie C, Shiguang S, Chu H, Guoying Z, Pietikainen M, Xilin C, Wen G (2009) WLD: a robust local image descriptor. IEEE Trans Pattern Anal Mach Intell 32(9):1705–1720. doi:10.1109/tpami.2009.155
Li S, Gong D, Yuan Y (2013) Face recognition using Weber local descriptors. Neurocomputing 122(0):272–283. doi:10.1016/j.neucom.2013.05.038
Chang J-D, Yu S-S, Chen H-H, Tsa C-S (2010) HSV-based color texture image classification using wavelet transform and motif patterns. J Comput 20:7
Joyce Van De V (2001) Fundamentals of digital signal processing with Cdrom. Prentice Hall, Upper Saddle River
Maji P, Ghosh A, Murty MN, Ghosh K, Pal S, Pal A, Das N, Sarkar S, Gangopadhyay D, Nasipuri M (2013) A new rotation invariant weber local descriptor for recognition of skin diseases. In: Pattern recognition and machine intelligence. Lecture notes in computer science, vol 8251. Springer, Berlin, pp 355–360. doi:10.1007/978-3-642-45062-4_48
Brodatz P (1999) Textures: a photographic album for artists and designers. Dover Publications, USA
Ojala TMT, Pietikainen M, Viertola J, Kyllonen J, Huovinen S (2002) Outex-new frame work for empirical evaluation of texture analysis algorithm. In: Paper presented at the international conference on pattern recognition
Kristin JD, Bram van G, Shree KN, Jan JK (1999) Reflectance and texture of real-world surfaces. ACM Trans Graph 18(1):1–34. doi:10.1145/300776.300778
Gertjan JB, Jan-Mark G (2009) Material-specific adaptation of color invariant features. Pattern Recogn Lett 30(3):306–313. doi:10.1016/j.patrec.2008.10.005
Xiaoyang T, Bill T (2010) Enhanced local texture feature sets for face recognition under difficult lighting conditions. Trans Img Proc 19(6):1635–1650. doi:10.1109/tip.2010.2042645
Zhenhua G, Lei Z, David Z (2010) A completed modeling of local binary pattern operator for texture classification. Trans Img Proc 19(6):1657–1663. doi:10.1109/tip.2010.2044957
Dharmagunaw C, Mahmoodi S, Bennett M, Niranjan M (2013) Rotation invariant texture descriptors based on Gaussian Markov random fields for classification. Pattern Recognit Lett 69:15–21
Song K, Yan Y, Zhao Y, Liu C (2015) Adjacent evaluation of local binary pattern for texture classification. J Vis Commun Image Represent 33:323–339. doi:10.1016/j.jvcir.2015.09.016
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Masoudi, B. Classification of color texture images based on modified WLD. Int J Multimed Info Retr 5, 117–124 (2016). https://doi.org/10.1007/s13735-016-0097-4
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DOI: https://doi.org/10.1007/s13735-016-0097-4