Optimized Bounding box fitting around an object is necessary for accurate localization of the Region of Interest (ROI), so that features extracted from the ROI are useful for many computer vision applications. Current methods tend to be inefficient, imprecise, and with high computational complexity. In this work a novel algorithm is presented that is designed for fitting a bounding box around an object that covers maximum part of the object as ROI. The improvement in inserting bounding box enhances the process of recognizing, tracking, and classifying objects, which is highly valuable for applications such as surveillance, autonomous driving, and security. In this work we are proposing a novel algorithm for fitting a bounding box around an object to maximize the object area covering and for minimizing the background clutter as a part of ROI.