This paper presents a text line segmentation method for printed or handwritten historical Arabic documents. Documents are first classified into 2 classes using a K-means scheme. These classes correspond to document complexity (easy or not eas

迫零和最小均方误差比较，非常好的程序，保证可以仿真出图形-DIP text book kmeans image segmentation Input: ima: grey color image k: Number of classes Output: mu: vector of class means mask: