The unique heat radiation of infrared image is generated from subcomponents . this paper analyses the natural feature of infrared image and the relationship between the shape and orientation with eigen vectors , gives the measure to classify infrared image based on object position to improve ability of compatibility in object recognition , moreover , applies the independent component for sub - region segmentation to construct new infrared image eigen vectors . the image features are processed by a support vector machine , and transform the binary svm to multi - object classifier 文中在傳統(tǒng)紅外熱圖像特征量的基礎之上,通過分析紅外熱圖像自身特性以及它的形成與其自身姿態(tài)的關系,提出了對目標物體紅外熱圖像基于目標姿態(tài)的子分類,來提高目標識別中對姿態(tài)的容忍度;同時根據(jù)紅外目標子部件對圖像影響的統(tǒng)計獨立性,使用獨立元的方法對目標紅外熱圖像進行了子區(qū)域分割,形成了新的紅外圖像特征量。