A New Histogram-based Kernel Function Designed for Image Classification
Jia Shi-jie①② Kong Xiang-wei①
①(Faculty of Electronic Information & Electrical Engineering, Dalian University of Technology, Dalian 116023, China) ②(College of Electrical & Information, Dalian Jiaotong University, Dalian 116028, China)
Abstract：Kernel-based Support Vector Machine (SVM) is widely used in many fields ( e.g. image classification) for its good generalization, in which the key factor is to design effective kernel functions. As there is not much a priori knowledge introduced into traditional kernel functions, the data-driven kernel building method is proposed to construct a new histogram kernel function which is combined with Bag OF Word (BOW) model and based on TF-IDF Weighted Quadratic Chi-squared (WQC) distance. In the process of calculating distances between histograms, the distinct discriminative power of each histogram bin is fully taken into consideration to boost classification performance of kernel functions. Experiments on several classic image data sets (Caltech101/256, etc.) show the better classification performance of the proposed method.
贾世杰, 孔祥维. 一种新的直方图核函数及在图像分类中的应用[J]. 电子与信息学报, 2011, 33(7): 1738-1742.
Jia Shi-Jie, Kong Xiang-Wei. A New Histogram-based Kernel Function Designed for Image Classification. , 2011, 33(7): 1738-1742.
2011, Vol. 33 
