Inability to identify objects accurately for a long time has been a challenge to claiming ownership, justice, and securing life and property. Previous methods employed to provide solution to these problems proved unsatisfactory. Many of the algorithms used in the previous methods could no longer handle the challenges confronting today’s identification tasks. This paper is a novel approach to detecting object whether static or on motion in web camera. The algorithmic program used was developed using OpenCV python modules. Initial and subsequent captured object’s images were saved in a frame before converting them to Gaussian blur images. The difference between the initial and subsequent images was calculated and their threshold defined to remove the shadows and other noises. Borders of the objects were defined before a rectangular box was added around the object. Then, the time when the object appeared and exited the camera was also calculated.