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Due to low brightness, the performance of autofocus will serious decline in low contrast images, making it quite difficult to locate the focus region. To tackle this challenge in computer vision, we perform autofocus by conducting a salient object detection method. Based on the mechanism of human visual system, salient object is detected by calculating global saliencies in superpixels. First, the...
Saliency computational model with active environment perception can substantially facilitate a wide range of applications. Conventional saliency computational models primarily rely on hand-crafted low level image features, such as color or contrast. However, they may face great challenges in low lighting scenario, due to the lack of well-defined feature to represent saliency information in low contrast...
The goal of salient object detection is to estimate the regions which are most likely to attract human's visual attention. As an important image preprocessing procedure to reduce the computational complexity, salient object detection is still a challenging problem in computer vision. In this paper, we proposed a salient object detection model by integrating local and global superpixel contrast at...
Traffic sign recognition plays an important role in autonomous vehicles as well as advanced driver assistance systems. Although various methods have been developed, it is still difficult for the state-of-the-art algorithms to obtain high recognition precision with low computational costs. In this paper, based on the investigation on the influence that color spaces have on the representation learning...
This paper presents a novel classification method for high-spatial-resolution satellite scene classification introducing multiset aggregated canonical correlation analysis (MACCA)-based feature fusion to fuse and combine multiple features. Firstly, a superpixel representation of the scene is constructed by employing a high-efficiency linear iterative clustering algorithm. After that, three diverse...
In security surveillance video (SSV), foreign object occlusion is increasingly common. Automatic detection of suspicious occlusion has become important. In this paper, a banner occlusion detection approach is proposed. The proposed approach first detects the banner in the image using both color feature and shape feature. More specifically, the proposed approach exploits the HSV color space to extract...
Visual saliency is an important cue in human visual system, it can identify salient region in image. Image contrast has been utilized as an effective feature to detect the salient region. The conventional contrast measures utilize both spectral and spatial properties of image in many salient region detection methods. However, they only consider the local characteristics of image region, consequently,...
An adaptive salient region detection method is proposed in this study, which combines LAB and RGB feature space and fused the color and contrast features. This algorithm first extracts the color feature of each image block in the LAB space and the contrast feature in the RGB space, and then fuses the color feature saliency map and the contrast feature saliency map using the principal component analysis...
The article is to demonstrate a way to detect moving objects in dynamic scene. This method integrates the means of background difference and level set. First, we adopt background difference, which is to connect the color of video image and movement mode, and then we can renew the dynamic scene by judging the threshold so that the foreground contour initial model can be obtained. Next, the level set...
We present a fusion approach in the gradient domain to combine complementary advantages between image enhancement results for visualization improvement. A weighted structure tensor is employed to capture significant details of each input channel, and local contrast is incorporated in the design of fusion weights. Experimental results demonstrate that the fused image can preserve significant detail...
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