关键词: 维吾尔文, 手写文本图像, 单词切分, 聚类, 着色处理

Abstract: For the problem of word extraction from handwritten Uyghur text lines, this paper proposes a clustering algorithm based on FCM fusion K-means. Through the clustering, two classification can be obtained for within word distance and between word distance. Based on clustering results, merging the connected components to get the segmented points. At the same time for the connected components which are within the segmented points used connected components labeling and coloring. In this paper, experimental object is 50 pairs of Uyghur off-line handwritten text images that are written different people and there are 536 lines and 4,002 words, correct segmentation rate reaches 80.68%. Experimental results show that the proposed method solve the problem which is difficult to extract words from the text line because of irregular distance between the words and overlapping between adjacent words. Meanwhile the presented method achieves whole dispose to the large handwritten text image.

Key words: Uyghur, handwritten text image, word extraction, clustering, coloring