the flow diagram of fig2 the first time the algorithms 5 are executed in the server their count variable is set to one this variable controls the sub image of the plurality of sub images 1 n of the image 2 which will be selected and will increase as the image 3 to be recognized is not matched to a sub image the order for selecting each one of the sub images 1 n is estimated according to the probability where the image to be recognized 3 will appear in the image 2 in the real world the likelihood that the image 3 is in the middle is generally higher than it would appear in the upper left corner as a result the image is divided into the sub images 1 n with estimated probabilities as shown in the fig3 the probabilities can be dynamically updated in case of tracking to put the highest probability of finding the object we are looking for in the closest sub regions to the previous processed frame sub regions the first sub image is passed to the algorithms 5 where it will be processed using several image processing procedures which can be characterized as pre processing for example in order to process the image before applying one of the methods existing for feature extraction a conversion from rub or bgr to gray scale can be applied and later a filter for blurring.