Object detection involves detecting the instances of objects from a particular class in the image. The goal of object detection is to detect all instances of objects from known class, such as people, cars or faces in an image. Object detection using haar feature based cascade classifier is an effective object detection method. It is a machine learning based approach where a cascade function is trained from lots of positive and negative images. It is used to detect the objects in other images. In this work, we propose a new application for on-road moving object detection in the goal to participate in reducing the big number of road accidents. Road moving object detection in traffic video is a difficult task. Hence, in this work, we present a system in order to control the outside car risks by detecting the different road moving objects. Experimental results indicate that suggested method object detection can be achieved with a high detection ratio.