Abstarct: In this study, several image processing techniques have been studied for the mine scale exploration for chromites deposits. Traditional exploration methods are baxsed on gravity, magnetic and structural geology, which suffer several shortcomings, including lack of sufficient geophysics methods. This is because of almost equal density of rocks containing chromites. The method introduced by Kravchenko (in Kimbersai chromite deposit) is a qualitative method and cannot be automated. Obtaining a data baxse, baxsed on this method by optical method is time consuming and costly. The other reasons could be addressed by the existence of different kind of ore deposits and uncertain exploration status of many chromites deposits. These shortcomings make the interpretation process time consuming and costly, as well. The proposed technique in this research requires nothing more than an ore microscope fitted with a digital camera, and a PC which will run off – the shelf image processing software. This method works, despite the fact that the image analysis technique includes a wide range of mineral substances from sulfide to coal, iron to rare elements and diamond, and from bauxites to clay. Using the image processing technique, color, brightness and morphometery analysis can be done in a quantitative method. Because optical characteristic and physical phenomena of minerals can be explained more clearly. We outline here a relatively automated method, which uses standard image processing techniques to acquire size, shape and model data for chromites phenocrysts and voids in a suite of donate Alpyan, in Faryab mine area (SE Iran). baxsed on the proposed method estimated and calculated geometric attributes (parameters) of minerals and natural elements in microscopic and low density scale are stored in a data baxse. This is baxsed on their brightness and morphometery properties by a computer baxsed optic-geometric image processing method. Computationally, the introduced technique make possible, without exploration drilling, the distinction between blind mineralization and false ore mineralization. The methodology developed in this research has been verified by testing it on various real – world mining geology projects. The end result of this study gives promises for chromites exploration in mine scale using an algorithmic digital image processing technique.