Abstract
Salient object detection has become an important direction in image processing and computer vision. The traditional center-priori theory believes that salient target should be closer to the central area of the image. However, false detection will often occur when the salient object is closer to the image boundary. So, this paper obtains center coordinates of the salient object by using Harris corner detection algorithm and convex hull. Accordingly, an improved center-priori saliency detection model is obtained by applying the frequency-tuned method. And then, the local saliency is set up by wavelet transforming which has the local characteristic information representation ability in the time domain and frequency domain. In addition, we obtain the global saliency by spectral residual analyzing. Finally, an advanced center-priori saliency model is established. The experimental results show that the model in this paper has better detection effects and higher target detection rates.
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