首页> 外文期刊>International Journal on Smart Sensing and Intelligent Systems >A HYBRID FUZZY MORPHOLOGY AND CONNECTED COMPONENTS LABELING METHODS FOR VEHICLE DETECTION AND COUNTING SYSTEM
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A HYBRID FUZZY MORPHOLOGY AND CONNECTED COMPONENTS LABELING METHODS FOR VEHICLE DETECTION AND COUNTING SYSTEM

机译:车辆检测与计数系统的混合模糊形态学和连通分量标记方法

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A hybrid fuzzy morphology and connected components labeling method is proposed for detecting and counting the number of vehicles in an image taken from a traffic monitoring camera. A fuzzy morphology approach in image segmentation method is used in the system to achieve faster computation time compared to the supervised learning. The connected components labeling method is combined with a fuzzy morphology method to determine the region and number of objects in an image. The processing phases in the proposed system are image preprocessing, image segmentation, and vehicle detection and counting the number of vehicles. Images are captured from the traffic monitoring cameras installed in highways. Results from testing phase using thirty images with varying brightness, contrast, and quality taken from different cameras during daylight showed that the accuracy of the system in counting the number of vehicles is 78.21%.
机译:提出了一种混合模糊形态学和连通零件标注方法,用于对交通监控摄像机拍摄的图像中的车辆数量进行检测和计数。与监督学习相比,系统中使用了图像分割方法中的模糊形态学方法来实现更快的计算时间。连接的组件标记方法与模糊形态学方法相结合,以确定图像中对象的区域和数量。所提出的系统中的处理阶段是图像预处理,图像分割,车辆检测以及车辆数量的计数。图像是从高速公路上安装的交通监控摄像机捕获的。测试阶段使用三十张不同亮度,对比度和质量的图像在白天进行测试的结果表明,该系统在计算车辆数量时的准确性为78.21%。

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