Improved Integrated Feature Congruency Model and its Application

Interesting target detection algorithm in complex natural backgrounds images is studied in this paper. Firstly, logGabor filter bank is analyzed, which is consistent with human visual system characteristics. Several kinds of local features from the filter bank can form the integrated feature. Integrated feature congruency (IFC) model is established. And upon compensating noise for IFC, an improved integrated feature congruency (IIFC) model is obtained, in which, target detecting is translated to find the interest points that are significant across scales and orientations. This model is applied to complex natural backgrounds images for target detection. Experimental results show that this method can detect interesting targets effectively from complex natural backgrounds scenes.