TY - JFULL AU - Andr谩s Barta and Istv谩n Vajk PY - 2007/8/ TI - Integrating Low and High Level Object Recognition Steps by Probabilistic Networks T2 - International Journal of Computer and Information Engineering SP - 2112 EP - 2122 VL - 1 SN - 1307-6892 UR - https://publications.waset.org/pdf/15671 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 7, 2007 N2 - In pattern recognition applications the low level segmentation and the high level object recognition are generally considered as two separate steps. The paper presents a method that bridges the gap between the low and the high level object recognition. It is based on a Bayesian network representation and network propagation algorithm. At the low level it uses hierarchical structure of quadratic spline wavelet image bases. The method is demonstrated for a simple circuit diagram component identification problem. ER -