@inproceedings{9e99ef43d9704b149d34be18b392f66c,
title = "Analysis of correlation between image texture and friction coefficient of materials",
abstract = "It is unknown that whether friction coefficients of materials can be predicted by their images. In this paper, we explore the correlation between the image gray-level and the friction coefficient of materials. We introduce a systematic approach to find the correlation model. First, four key features were extracted from Gray-Level Co-occurrence Matrix (GLCM) using Hue Saturation Intensity (HSI) color space. Second, BP neural network was utilized to establish the correlation model between the image gray-level and the friction coefficient. The proposed approach was validated using a dataset with 100 samples. The results show that the average regression error of the model is 16.7\% for the 100 samples, and 2.8\% for the subset of 30 fabric samples among the totals. Within those fabric samples, the prediction error for new samples is 20.1\%. The experimental results indicate a possibility of inferring the friction coefficient from the image of the material. This study might provide a way of automatically constructing a haptic database through the large amount of images on the internet.",
keywords = "GLCM, feature extraction, haptic modeling, neural network",
author = "Pengzhi Zhang and Dangxiao Wang and Yuru Zhang",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Imaging Systems and Techniques, IST 2017 ; Conference date: 18-10-2017 Through 20-10-2017",
year = "2017",
month = jul,
day = "1",
doi = "10.1109/IST.2017.8261507",
language = "英语",
series = "IST 2017 - IEEE International Conference on Imaging Systems and Techniques, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1--6",
booktitle = "IST 2017 - IEEE International Conference on Imaging Systems and Techniques, Proceedings",
address = "美国",
}