本文提出一個將影像以區域方式分割的方法，並且針對每個區域內的每個像素相互作同質性計算，來得到該區域的的主體色彩資訊，利用區域主體色彩資訊建構背景模型以偵測複雜背景下的移動物體。影像序列初期要建構背景模型，需要單張或數張只有背景的影像來擷取區域的色彩資訊以建立背景模型，並且利用影像的紋理資訊來處理複雜的背景，可以因應背景的變化來更新背景模型，克服複雜背景下的變化。傳統的編碼簿演算法在處理複雜背景情況下，雖然效果不錯，但是需要較多時間及計算複雜度。我們的方法跟其他背景模型物件分割技術相比，都能夠在複雜的背景環境下更為快速地分割出移動物體。 This paper presents a block-based image segmentation method. The homogeneity of all the pixels in a block are calculated, and the color information of the block can be obtained. Thus, the background model can be built, and a moving objects can be detected accordingly in a complex background. In an image sequence, some background images are used to capture blocks’ color information to create the background model. Their texture information is applied to process a complex background. The background model can be updated while background changes. The traditional codebook background method useds complex algorithms, and requires more time and memory. Compared to other segmentation methods, our approach with the background model can segment a moving object rapidly and successfully in a complex background environment.
