The mining of stable image feature-compositions in object recognition
目标识别中的稳定图像特征组合发掘

In order to improve the stability and discrimination of local feature combination for image representation,two image mediate-level representations,Inter-CSP(inter-class common stable pattern) and ntra-SSP(intra-class special stable pattern) are proposed.The details of processing are given,which can be divided into statistic-filtering,pattern decomposition,pattern summarization,and item-based geometric relation modeling on frequent item_sets mined from image semi-local features.A recognition framework is introduced based on Inter-CSP and Intra-SSP.The experiment results demonstrate that these two kinds of patterns are superior to classical methods.