Vehicle Detection using Upper Local Ternary Features with SVM Classification

Linn Linn Thike, Thin Lai Lai Thein
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引用次数: 0

Abstract

Local Ternary Pattern (LTP) is an extension of Local Binary Pattern (LBP), which is known as a standard textural descriptor for various recognition systems. There are a lot of usages of LBP and LTP in the variety of pattern recognition in different fields. It is also efficient features for vehicle detection, recognition and monitoring. This paper proposed an algorithm that applied the operator to upper LTP (upper-LTP) matrix as feature vector to calculate instead of pattern stream generation. This paper analyzes the accuracy rate between the Complemented- Uniform Local Binary Pattern (Complemented-ULBP) which is our previous work, Uniform Local Binary Pattern (ULBP), simple Local Binary Pattern (LBP) and the proposed system, Upper-LTP, with SVM classification.
基于SVM分类的上局部三元特征车辆检测
局部三元模式(LTP)是局部二元模式(LBP)的扩展,是各种识别系统的标准纹理描述符。LBP和LTP在不同领域的模式识别中有着广泛的应用。它还具有高效的车辆检测、识别和监控功能。本文提出了一种将算子应用于上LTP (upper-LTP)矩阵作为特征向量进行计算而不是生成模式流的算法。本文分析了我们之前研究的互补-均匀局部二值模式(complementen -ULBP)、均匀局部二值模式(ULBP)、简单局部二值模式(LBP)和提出的系统Upper-LTP在SVM分类中的准确率。
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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