In recent technologies, object detection is considered as an effective tool for diagnosing the anonymous activities of a particular location. We can recognize the specific object from images and videos. Therefore, we can obtain essential information for developing a highly secure framework. The ODEF technique is developed for enhanced object detection and classification process. By utilizing the proposed technique, the anonymous activities in a specific region can be detected through the video. This technique detected the objects with bounding boxes; therefore, malicious activities can be shown in distinct visual. Then, the utilization of DRCNN technique provides better platform to classify the object.