III WVC 2007 - Iris.sel.eesc.sc.usp.br - USP

WVC'2007 - III Workshop de Visão Computacional, 22 a 24 de Outubro de 2007, São José do Rio Preto, SP.For vehicles with great length, two methods are beingexperimented in this first case. One solution is theuse of wide angle lens that allows detecting in a singleframe vehicles with great length. Another approach isthe use of a combinations of sequential frames methodfor those vehicles longer than the capturing area.This task is made with a fuzzy controller with rulesfor each class of vehicle. Each rule has as inputs: thenumber of axles and the distance between them, see figure5; and the vehicle class as output.5. Axles detectionDetecting axles is a task that falls in patterns recognitionarea. The haartraining functions set[1] providedwith OpenCV library were used to do this.OpenCV uses such a statistical approach for objectdetection. This method uses simple Haar-like features(so called because they are computed similar to the coefficientsin Haar wavelet transforms) and a cascade ofboosted tree classifiers as a statistical model [9]. Thismethod is tuned and primarily used for face detection.Therefore, a classifier for an arbitrary object class, likevehicles tires, can be trained and used in exactly thesame way.The cascade training was done using about 7000 imagesof positives, images containing exclusively vehiclestires, and about 3000 images of negatives, images notcontaining vehicles tires.Figure 5. Example of distance between axles inputcode.The use of a fuzzy controller allows that we workunder imprecise information, so we just lead the inputof distance between axles as not precise adjectives likelittle, medium and big instead of numeric values. Eachclass of vehicle has a specific rule, see figure 6.Figure 4. Detected axles are circledThen is possible to find how much axles the vehiclehave, the diameter of the tires, and distances betweenthem, see figure 4.6. ClassificationWith the contour of the vehicle, the number of axlesand the distance between them is possible to determinein which class the vehicle is.Figure 6. Example of rule code.245