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Local Binary Patterns | Image Processing #16 | HBY coding academic
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In this video, we introduce the local binary patterns (LBP, for short). When doing texture analysis or face recognition, LBP plays an important rule in these processes.
In most cases, we don't compare the LBP results, but compare its histogram. For example, we want to do face recognition. We should make histograms in term of some specific regions (eyes, nose, mouth, ears...), and compare these histograms with others'. If there exists an histogram set is mostly similar, then it is indicated that these two are quite similar (these two are same person's face).
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在這部影片中，我們將介紹局部二值模式(Local Binary Patterns)，它在紋理特徵分析或是人臉辨識中，扮演著重要的角色。
在大多數的情況中，我們不直接比較LBP的結果，而是比較LBP的直方圖結果(亦即，LBP中不同顏色所佔比例的統計結果)。舉例來說，如我們要做人臉辨識。我們應該要建立LBP中，人臉特徵區域(眼睛、鼻子、嘴巴、耳朵...)的直方圖。如此，有了這些統計資訊，可以利用一些評估函數，來判斷它與其它張圖像是否相似、相似程度多少。當找到一個與它非常相似(假設是99.999%)，就可以說它是同一張臉。
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