基于视觉的轮胎胎面深度检测

IF 1.4 4区工程技术 Q3 ENGINEERING, MECHANICAL

Transactions of FAMENA Pub Date : 2021-01-01 DOI:10.21278/tof.453024420

Emina Petrović, Danijela Ristić Durrant, M. Simonović, Ž. Ćojbašić, V. Nikolic

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引用次数: 1

摘要

本文在现有图像处理技术的基础上，提出了一种轮胎胎面深度的视觉、非接触自动检测方法。利用定向梯度直方图对图像进行特征提取。为了分析哪一组特征给出了最好的分类结果，使用不同的像素数和每个块的单元数训练和测试了一个线性支持向量机分类器。本文给出了得到的处理结果和实验结果。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Vision-Based Inspection of Tyre Tread Depth

In this paper, an approach for visual, non-contact automatic inspection of tyre tread depth based on existing image processing techniques is presented. Histograms of oriented gradient are used for feature extraction from images. In order to analyse which set of features gives the best classification results, a linear support-vector machine classifier was trained and tested using different numbers of pixels and numbers of cells per block. The obtained processing and experimental results are presented in this paper.

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来源期刊

Transactions of FAMENA 工程技术-材料科学：综合

CiteScore

2.20

自引率

30.80%

发文量

审稿时长

>12 weeks

期刊介绍： The journal publishes research and professional papers in the following fields: Aerospace Engineering; Automotive Engineering; Biomechanics; Energetics; Engineering Design; Experimental Methods; Industrial Engineering; Machine Tools and Machining; Materials Science; Mathematical Modelling and Simulation; Mechanical Design; Mechanics & Fluid Mechanics; Nanotechnology; Naval Architecture; Numerical Methods; Process Planning; Quality Assurance; Robotics & Mechatronics; Thermodynamics.