Research of Fast FCM Vehicle Image Segmenting Algorithm Based on Space Constraint

Bin Zhou, Tuo Wang, Shijuan Pan
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引用次数: 1

Abstract

Vehicle identification and traffic accident detection plays an important role in the Intelligent Transportation System. Vehicle image segmentation is the key technological foundation for further identification and detection processing. This article improves the inadequacy of Fuzzy C-Means (FCM) clustering algorithm by proposing the Spatial Constrained FCM (SCFCM) algorithm. Firstly, the each pixel's membership degree is corrected according to its field pixels', eliminating the impact of noise on the accuracy of FCM clustering. Secondly, a new searching algorithm based on Gaussian model single-peak judgment is proposed to obtain the optimal number of clusters. After that, initial membership matrix creation algorithm is used to reduce iteration times. The performance of the experiments shows that method is effective.
基于空间约束的快速FCM车辆图像分割算法研究
车辆识别和交通事故检测在智能交通系统中占有重要地位。车辆图像分割是进一步识别和检测处理的关键技术基础。针对模糊c均值(FCM)聚类算法的不足,提出了空间约束FCM (SCFCM)聚类算法。首先,根据每个像素的场像素对其隶属度进行校正,消除噪声对FCM聚类精度的影响;其次,提出了一种基于高斯模型单峰判断的聚类搜索算法。然后,采用初始隶属矩阵创建算法,减少迭代次数。实验结果表明,该方法是有效的。
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