Patent ID: 8238650

Claim:
A computer based method for determining an object segment of an object represented in an electronic image, comprising the steps of: forming a multitude of binary maps obtained from a multitude of basic filter maps via unsupervised learning of a multi-feature segmentation, the step of unsupervised learning of a multi-feature segmentation further comprising the steps of: forming training data vectors {right arrow over (m)} (x,y) using basic filter maps (F i ); obtaining codebook vectors {right arrow over (c)} j from the training data vectors {right arrow over (m)} (x,y) using a vector quantization network (VQ); generating adaptive topographic activation maps (V J ) from the training data vectors {right arrow over (m)} (x,y) and the codebook vectors {right arrow over (c)} j , the adaptive topographic activation map (V J ) being scene dependent and computed as V j (x,y) =∥{right arrow over (m)} (x,y) −{right arrow over (c)} j ∥ 2 ; forming a relevance map that serves as a prediction mask for a region around the object and computed as a superposition from a center map and a disparity map; forming a selection of segments from the multitude of binary maps using the relevance map as a selection criterion; and forming an object map based on the selection.