Optimization of Salient Object Segmentation by using the influence of color in Digital Image

Human attention is more likely to be interested indifferent objects or striking in image processing called salientobject. Existing approaches worked well in finding the salientobject in this image, but they have not been able to accuratelydetect where objects should stand out due to the influence of lightintensity, there are various object results of salient object detectionin which area is still cut off or do not appear because they do notinclude salient area. We offer solutions to fix these problems byoptimizing salient object detection prioritizing object area aftersalient area, through checking comparison of the color regionlocated around the area of the salient. This Optimization of theapplication is able to improve to 83% from 100 salient object whichhas this problem, and able to produce more natural Saliency Cut

Saliency difference based objective evaluation method for a superimposed screen of the HUD with various background

The head-up display (HUD) is an emerging device which can project information on a transparent screen. The HUD has been used in airplanes and vehicles, and it is usually placed in front of the operator's view. In the case of the vehicle, the driver can see not only various information on the HUD but also the backgrounds (driving environment) through the HUD. However, the projected information on the HUD may interfere with the colors in the background because the HUD is transparent. For example, a red message on the HUD will be less noticeable when there is an overlap between it and the red brake light from the front vehicle. As the first step to solve this issue, how to evaluate the mutual interference between the information on the HUD and backgrounds is important. Therefore, this paper proposes a method to evaluate the mutual interference based on saliency. It can be evaluated by comparing the HUD part cut from a saliency map of a measured image with the HUD image.Comment: 10 pages, 5 fighres, 1 table, accepted by IFAC-HMS 201