A novel superpixel based color spatial feature for salient object detection

Human visual system has the ability to detect objects of interest in real time with a very high accuracy. It becomes an arduous task for a machine to mimic the same. There is a tradeoff between detection accuracy and computation time, while detecting salient objects. The authors made an attempt to develop a model which in least amount of time could produce better detection accuracy. In the proposed, SLIC algorithm is used to decompose an image into superpixels which are used to generate a color spatial feature, which is further combined with the center based position prior to form the saliency map. The proposed model is matched with seventeen related models on six publicly available datasets. The experimental section shows that the proposed model generates the best results when compared in terms of area under curve, recall, precision and F-measure on all the six datasets. It is also better among many models in terms of computation time.