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We present in this paper a comparative study of two segmentation methods of handwritten Arabic text. The first method is a combination of the Mathematical Morphology (MM) and the algorithm of construction of the Outer Isothetic Cover of a digital object (OIC) named MM-OIC. The second method uses the Hough Transform (HT) and MM to segment the handwriting Arabic script called HT-MM. These methods are applied in two levels of segmentation: text lines and Pieces of Words. The two proposed methods are evaluated and compared to a set of documents selected from three databases: IFN/ENIT-database (17 documents), BSB (16 documents) and KSU (30 documents) online databases. The average rate line segmentation of MM-OIC is 75%, and of HT-MM is 45%. The average rate of PAW segmentation acheive 89% for the MM-OIC and 70% for the HT-MM method. The efficiency of the MM-OIC method is explained by the fact that this method can extract the approximate form of writing, and sometimes it can exceed some problems that are related to the Arabic script such as the overlapping lines and diacratical symbols.