ANN Approach for Classification of Different Origin Fabric Images

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Basavaraj S. Anami 1,* Mahantesh C. Elemmi 2

1. K.L.E. Institute of Technology, Hubballi, 580030, India

2. Jain College of Engineering and Research, Belagavi, 590008, India

* Corresponding author.


Received: 26 Jul. 2019 / Revised: 2 Aug. 2019 / Accepted: 23 Aug. 2019 / Published: 8 Dec. 2019

Index Terms

Morphology, Plant origin, Animal origin, Mineral origin, Feature extraction, ANN.


This paper focuses on classification of varieties of plants’, animals’ and minerals’ origin fabric materials from images. The morphological operations, namely, erosion and dilation are used. ANN classifier is used to predict the classification rates and the rates of 89%, 87% and 88% are obtained for plants’, animals’ and minerals’ origin fabric images respectively. The overall classification rate of 88% is obtained. 

Cite This Paper

Basavaraj S. Anami, Mahantesh C. Elemmi, " ANN Approach for Classification of Different Origin Fabric Images", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.12, pp. 29-38, 2019. DOI: 10.5815/ijigsp.2019.12.04


[1]Wang, Xin, Ge Wu, and Yueqi Zhong. "Fabric Identification Using Convolutional Neural Network." In International Conference on Artificial Intelligence on Textile and Apparel, pp. 93-100. Springer, Cham, (2018).

[2]Xiang, Zhong, Jianfeng Zhang, and Xudong Hu. "Vision-based portable yarn density measure method and system for basic single color woven fabrics." The Journal of The Textile Institute, pp.1-11.(2018)

[3]Singh, Anamika, Manminder Singh, and Birmohan Singh. "Face detection and eyes extraction using sobel edge detection and morphological operations." In Advances in Signal Processing (CASP), Conference on, pp. 295-300. IEEE,( 2016).

[4]Sparavigna, Amelia Carolina. "Image Segmentation Applied to the Analysis of Fabric Textures." Philica (2016).

[5]Hasan, Syed Mohammad Abid, and Kwanghee Ko. "Depth edge detection by image-based smoothing and morphological operations." Journal of Computational Design and Engineering3, no. 3: pp. 191-197. (2016)

[6]Guo, Ying-Ying, Xin-Jie Wang, Yu-Sheng Zhai, Cai-Dong Wang, Liang-Wen Wang, Feng-Xiao Zhai, Kun Yan et al. "A novel method for identification of cotton contaminants based on machine vision." Optik-International Journal for Light and Electron Optics 125, no. 6 : pp. 1707-1710.(2014).

[7]Zhang, Jie, Binjie Xin, and Xiangji Wu. "A review of fabric identification based on image analysis technology." Textiles and Light Industrial Science and Technology (2013).

[8]Aziz, Mahmoud Abdel, Ali S. Haggag, and Mohammed S. Sayed. "Fabric defect detection algorithm using morphological processing and DCT." In Communications, Signal Processing, and their Applications (ICCSPA), 2013 1st International Conference on, pp. 1-4. IEEE, (2013).