Object detection in images using artificial neural network and improved binary gravitational search algorithm

In this paper, artificial neural network (ANN) and improved binary gravitational search algorithm (IBGSA) are utilized to detect objects in images. Watershed algorithm is used to segment images and extract the objects. Color, texture and geometric features are extracted from each object. IBGSA is used as a feature selection method to find the best subset of features for classifying the desired objects. The purpose of using IBGSA is to decrease complexity by selecting salient features. At last, selected features are used in the ANN for detecting objects. Experimental results on detecting hand tools show that the proposed method could find salient features for object detection.