This paper is focussed on detection, counting and classification of moving objects using differential and graphical techniques. The basic idea used is variation in the traffic flux density due to presence of objects in the scene. Accurate Traffic flux estimation will play vital role in object detection, counting and classification. The designed technique is evaluated with 15 different video sequences and weighed thoroughly with simple confidence measures. In the present work we have achieved real time analysis with normal video rate. And for object classification computation we are taking specific frame gap which saves computational time. The result produced with this analysis is extremely good and beneficial in real time traffic control, detecting and classifying objects in urban areas. The vehicle counting achieved with an accuracy of 94% under varied road conditions. In the normal condition the average accuracy achieved is near to 97%.