Abstarct: In this research, image analysis techniques are used to automate traditional process of identifying and microscopical studies for calculating the quantitative parameters of particles in polished sections. In first step, specimens were collected from iron deposits from Diyan Cu-Fe Deposits. Ten thin - polished sections were prepared from these specimens and these sections were studied by optical microscope. Microscopical studies showed that the main ore in samples is Hematite and main gangue is silica, and barite with fewer amounts. The samples were crushed and grinded in ten dimensional fractions, and were prepared polished sections from particles in each fraction, At first, This sections was studied by traditional methods by using optical microscope, and we calculated the quantitative parameters of particles, such as the number of particles (n), average length (L) and width (B) of particles, the average perimeter (P) and area (A) of particles, elongation (L/B), roundness (4πA/P2) and particularly degree of liberation. In subsequent step, for automating this boring process, we wrote image analysis code in MATLAB R2009a. This code can calculate these quantitative parameters in a short time. (several seconds). For validating and ensuring the accuracy of the image analysis code results, output results were compared with the results of manual calculating in one hundred actual images. Comparing the results, proved the accuracy of the code results, And proved that written code, can facilitate the process of calculating the quantitative parameters in microscopical assessment, thus, contains innovation in calculating degree of liberation baxsed on accurate area and algorithms that are used