Several image processing techniques have been applied in a mine scale exploration for chromite deposits. Traditional exploration methods are based on geophysical methods, which suffer several shortcomings, including lack of sufficient geophysical contrast?. An optic-geometric image processing program is developed for extracting structural properties of chromite minerals in polished sections. The estimated and calculated geometric attributes and parameters based on brightness and morphometric properties of minerals in microscopic scale are stored in a data base. Computationally, the distinction between blind mineralization and false ore mineralization is possible, without exploration drilling, by this method. The methodology developed in this research, has been validated by testing it on various real world scenarios. It includes the structures of ore fields and chromite deposits in large and mine scale. The end result of this study gives promises for chromites exploration in mine scale using an algorithmic image processing technique. The advantage of the proposed method is that a quantitative method is replaced by a qualitative one. This can lead to make optimal managerial and economical decisions.