Abstract
Image segmentation process for high quality visual saliency map is very dependent on the existing visual saliency metrics. It is mostly only get sketchy effect of saliency map, and roughly based visual saliency map will affect the image segmentation results. The paper had presented the randomized visual saliency detection algorithm. The randomized visual saliency detection method can quickly generate the same size as the original input image and detailed results of the saliency map. The randomized saliency detection method can be applied to real-time requirements for image content-based scaling saliency results map. The randomization method for fast randomized video saliency area detection, the algorithm only requires a small amount of memory space can be detected detailed oriented visual saliency map, the presented results are shown that the method of visual saliency map used in image after the segmentation process can be an ideal segmentation results.
Highlights
The researchers in recent years have made a lot of contentbased image and video image scaling method [1–7]
All this to get results saliency map are in the Pentium R Dual-Core CPU E8400 generated on individual PC. This got a lot of visual saliency results chart shows randomized visual saliency detection methods available in different levels of complexity of the original input image to obtain good results for image detection effect and visual saliency map, and by the paper randomized visual saliency detection methods produced results visual saliency map and Itti methods, Geforman methods were compared, and the resulting visual saliency map detected more clear and detailed
The randomized visual saliency detection method can quickly generate the same size as the original input image and detailed results of the saliency map
Summary
The researchers in recent years have made a lot of contentbased image and video image scaling method [1–7]. The literature [12] is based on machine learning methods to obtain the input of the original image visual saliency area These methods can accurately detect the original image smaller target, mainly used in target identification and target tracking. Computational and Mathematical Methods in Medicine systems saliency region detection related work, and only need to store the original input image and the system output saliency results figure required memory to be able to perform. The randomized algorithms can be performed on the graphics processing unit to achieve even parallel computing These advantages make the proposed efficient randomized visual saliency region detection method become used in video sequences in real time. The system has generated from the corresponding visual saliency map, thereby improving image content-based video scaling to generate the overall quality of the results
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