This work aims to segment touching components (TCs) which may occur between word letters of consecutive text-lines or those of words of the same line in Arabic manuscripts. The proposed approach is mainly based on two steps: 1) finding for a localized touching component its most similar model, stored in a dictionary with its correct segmentation, based on shape context descriptor, 2) segmenting the touching component based on central point of the found most similar model's parts. Tests are performed using a database of connection zones (1300 samples) and three metrics: Manhattan, Euclidean and Canberra distances. Experimental results have shown the effectiveness of the proposed touching component segmentation method in comparison to some related works. Our best achieved TC segmentation rate is of 94%.