DETEKSI RODA KENDARAAN DENGAN CIRCLE HOUGH TRANSFORM (CHT) DAN SUPPORT VECTOR MACHINE (SVM)

Sri Dianing Asri, Desi Ramayanti, A. Putra, Yohana Tri Utami
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Abstract

In the digital image processing, many methods have been developed, the purpose of developing these methods is how computers can detect and recognize objects in an image with a precisely and process them in a relatively short time. Wheels are components that are always present in every vehicle, whether the vehicle is a bus, car or truck, it must have wheels with the same shape. If a wheel can be detected and recognized then the vehicle recognition and classification can be determined. This research focuses on capturing circle images, detecting wheel circles by applying Circle Hough Transformation (CHT). This transformation is able to recognize the object based on its boundaries and is resistant to noise. After obtaining the image of the circle, the next step is to classify it into Wheels and NonWheels using the Support Vector Machine (SVM) method. The development of the wheel circle detection model on the side view image of this vehicle can be used as one of the first steps in research on wheel-based automatic vehicle recognition and classification systems.
在数字图像处理中,已经发展了许多方法,发展这些方法的目的是使计算机能够精确地检测和识别图像中的物体,并在相对较短的时间内对其进行处理。车轮是每辆车都有的部件,无论是公共汽车、轿车还是卡车,都必须具有相同形状的车轮。如果可以检测到并识别车轮,则可以确定车辆的识别和分类。本课题主要研究了利用圆霍夫变换(circle Hough Transformation, CHT)技术捕获圆图像,检测车轮圆。这种变换能够基于物体的边界来识别物体,并且能够抵抗噪声。在获得圆的图像后,下一步是使用支持向量机(Support Vector Machine, SVM)方法将其分类为Wheels和NonWheels。基于该车辆侧视图像的车轮圆检测模型的开发可以作为基于车轮的车辆自动识别与分类系统研究的第一步。
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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