No abstract

Human attention is more likely to be interested in different objects or striking in image processing called salient object. Existing approaches worked well in finding the salient object in this image, but they have not been able to accurately detect where objects should stand out due to the influence of light intensity, there are various object results of salient object detection in which area is still cut off or do not appear because they do not include salient area. We offer solutions to fix these problems by optimizing salient object detection prioritizing object area after salient area, through checking comparison of the color region located around the area of the salient. This Optimization of the application is able to improve to 83% from 100 salient object which has this problem, and able to produce more natural Saliency Cut.

Human attention is more likely to be interested in different objects or striking in image processing called salient object. Existing approaches worked well in finding the salient object in this image, but they have not been able to accurately detect where objects should stand out due to the influence of light intensity, there are various object results of salient object detection in which area is still cut off or do not appear because they do not include salient area. We offer solutions to fix these problems by optimizing salient object detection prioritizing object area after salient area, through checking comparison of the color region located around the area of the salient. This Optimization of the application is able to improve to 83% from 100 salient object which has this problem, and able to produce more natural Saliency Cut.

No abstract