IV. CONCLUSION Shapes detection method has been proposed in this paper. Its main objective is to differentiate basic shape such as circle, square and triangle in the given input image by merely employing computer vision techniques. This method utilize compactness as the shape indicator where the compactness for circle is fixed from 1 to 14, square‟s compactness is in range 15 to 19 and triangle‟s compactness is from 20 to 40. From the result in the Section III, the proposed method achieved 85% detection accuracy in the selected database. However, this method is sensitive to noise and lighting condition. Poor lighting condition image will bring complexity in Otsu‟s threshold algorithm and the outcome of the result is not desirable.