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Handwriting recognition is the ability of a computer to receive and interpret intelligible handwritten input. Recognition systems are divided into two categories: holistic approach and analytical approach. A holistic approach handles the whole input image, while analytical approach involves two steps namely; segmentation and combination. Handwriting recognition began long time ago mainly in Latin and Chinese characters. However, little effort has been devoted to Arabic characters. The domain of handwriting in the Arabic script presents unique technical challenges and has been given more attention recently than other domains. In respect to the above issue, this paper investigates two different feature extraction methods, Angular span method and Distance span method, which may represent the distribution of pixels in the word properly. Samples from IFN/ENIT benchmark dataset are used to evaluate both methods.