期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：7
页码：217-226
DOI：10.14257/ijhit.2016.9.7.20
出版社：SERSC
摘要：There are several types of transport on the road; vehicles, bikes, motorcycles (two and four wheels), kids' bikes, construction vehicles, etc. In this paper, we present an enhanced algorithm for the detection rate to classify the two-wheelers with riding people using the normalized cross correlation (NCC) and its application of histogram of oriented gradients (HOG). HOG descriptors which are one of the well known methods for object detection are the feature descriptor using edge intensity in a local region. Using the NCC algorithm which is used to make a match from template images, local weighting values are calculated from template cell features. And the combined cell features are classified by using a boosting algorithm (Adaboost). The improvement detection rates are confirmed through experiments using bicycles and motorcycles data set for the front direction.
