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The main problem facing security in crowded place involving individual and groups of people can associated it is the tracking of object. The problematic of this point will arise in public area such as airport, subway, train station and shopping mall. Existing screening procedure may produce false indications if the object is beyond immediate proximity of people security It also creates an issue of congestion if there is a lot of crowd and that becomes unmanageable. The target of process to detect object in public and private area for individual and groups of people, many video and image processing detection methods are presented by different researchers in recent past to detect the object resources. However, most of methods of literature suffered from the low accuracy and robustness issue. The development of robust and accurate detection method is the need of hour. This study is devoted to the development of same, the main methods to do it by using the two methods of fusion first the spatial domain fusion and the transformation methods with drawback for first method of spatial distortion and this drawback can be overcome by using the second method of fusion of transformation technique. In this paper, the method first focuses on uses the DWT or can say traditional process with Hoteling algorithm to get the fused image. Then after this the meta-heuristic search process will applied to find out the optimal harmony to create the new principle component to the input images. Which after these steps will uses to classification by using K- means support vector machines to create built in system of object classifier. The proposed method performs superior than the other traditional methods of detection.