人耳檢測是人耳識別以及基于內(nèi)容的圖像和視頻檢索的一項重要任務(wù)。本文提出了一
種將背景差分和膚色模型相結(jié)合的人耳檢測算法。算法首先在序列圖像中自動提取運動目標并進行人體檢測，然后經(jīng)過膚色分割進行人耳的粗定位，產(chǎn)生人耳候選區(qū)域。最后利用人耳檢測模塊判斷候選區(qū)域中是否含有人耳，以及獲得它們的位置、大小等信息。實驗結(jié)果表明，該算法是有效的。
[關(guān)鍵詞] 人耳檢測，自適應(yīng)背景模型，背景差分，膚色模型
[Abstract] Ear detection is an important task in ear recognition and content-based
image and video retrieval. In this paper, we propose a method using background
subtraction and skin color model. First, we drew the movement goal and detected the
human body automatically in the sequence picture, then make a localization roughly and
produce the candidate area of ear via skin color model. Finally, we utilized the module of
ear detection to judge whether to contain the ears of people in the candidate area or not,
and obtained the information of their position, size, etc. Experimental results could
demonstrate its effectiveness.
[key word] ear detection, self-adaptive background update model, background subtraction,
skin clor model