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Stereo matching is an active research area in computer vision for decades. Most of the existing stereo matching algorithms assume that the corresponding pixels have the same intensity or color in both images. But in real world situations, image color values are often affected by various radiometric factors such as exposure and lighting variations. This paper introduces a robust stereo matching algorithm...
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...
We present a new way to combine the propagated flow in image pyramid and dense correspondences from descriptor matching for large displacement optical flow estimation. Because the matches and the flow propagated from the coarser level in image pyramid are possibly wrong, our method uses color-based weighted linear interpolation to reduce the wrong initial flow and alleviate over-smoothing, instead...
This paper presents a series of enhancements to a color-coded structured light range sensor that increases the adaptability to complex and unconstrained scenes. First, the projected pattern is made more visible on colored objects by replacing the unique colored pattern with time-multiplexed pseudo-color channels. Second, an exposure fusion algorithm is used when acquiring images to allow the detection...
A video segmentation method based on strong target constrained video saliency (STCVS) is proposed in this paper. In order to detect the salient region fast and effectively, the proposed STCVS is extracted based on the extension of image saliency by enforcing the salient region constrained with the location, scale and color model of the target. Besides, according to the results of STCVS, the super-pixel...
Image-based information hiding technology has been extensively studied in recent years. In order to ensure the security of information transmission, image information hiding technology must have the characteristics of transparency, security and robustness. In this paper, an improved image-based information hiding method is proposed, which utilizes the imperceptibility of the human eye to the change...
Multimedia data piracy in the Internet is a growing problem, since it provides easy and fast data transmission. Watermarking is regarded as a solution to restrain unauthorized duplication or distribution data. Image watermarking research mostly focuses on grayscale images with an extension to color images. However, most of these techniques ignore dependencies between color channels. In view of this,...
Traditional dehazing algorithm based on dark channel prior may suffer weak robustness against the variation of hazy weather and may fail in bright regions. To resolve these issues, this paper proposes an improved adaptive dehazing algorithm based on dark channel prior. Our method can adaptively calculate dehazing parameter, such as the degree of haze removal. Here the dehazing parameters are local,...
To Improve the robust performance of visual tracking in various kind of scene, a novel method by harmony search and co-inference learning based on multi-cues was proposed. The candidate state was achieved by the harmony search and co-inference learning. Then the harmony memory vector corresponded the biggest fitness function was chosen as the state vector. Compared with the harmony search visual tracking...
In this paper we evaluate the robustness of perceptual image hashing algorithms. The image hashing algorithms are often used for various objectives, such as images search and retrieval, finding similar images, finding duplicates and near-duplicates in a large collection of images, etc. In our research, we examine the image hashing algorithms for images identification on the Internet. Hence, our goal...
Tracking-by-detection methods treat the target location as a classification problem in which the approach SVM + HOG shows a good performance. However, training a good SVM classifier is cost expensive. In this paper, we replace SVM by linear discriminant analysis (LDA) for classification where the mean and covariance of negative examples are evaluated only once. Not only the training is much cheaper,...
The change of appearance of the target object is one of important issue in visual tracking. It is because some factors such as camera motion, illumination change, motion change, occlusion, and size change are influenced to the object target during tracking. Recently, discriminative correlation filters (DCF) gave good results to handle these problems. Unfortunately, the DCF only works in the single-resolution...
Predicting traffic flows on multiple inter-city roads play a critical role in traffic management. Temporal patterns of traffic flow can dynamically change over time as a result of traffic management measures such as the construction of new roads. Given this possibility, it is sensible to use only recent data, instead of all past data. In this study, by incorporating the latent factor model into a...
In this work, a new image watermarking algorithm on colour images is proposed. The proposed algorithm divides a cover image into three colour bands of red, green and blue. Then the following tasks are done on all three channels separately. First, Each colour band is divided into patches of small sizes then the entropy of each patch is calculated. At this step a threshold is found based on the average...
Current approaches for text line segmentation often are either very specialized to specific domains or they depend on many parameters. More specifically, the extraction of text-lines with large sizes, i.e., headings and titles in the Arabic like script could not be segmented correctly by state-of-the-art methods. In this work, we present a simple and robust text-line segmentation approach. The proposed...
The automatic and precision classification for breast cancer histopathological image has a great significance in clinical application. However, the existing analysis approaches are difficult to addressing the breast cancer classification problem because the feature subtle differences of inter-class histopathological image and the classification accuracy still hard to meet the clinical application...
CAPTCHAs are applied on websites to differentiate between human users and automated programs, which indulge in spamming and other fraudulent activities. Since there are many websites that provide services in Arabic language, Arabic CAPTCHAs have been proposed by a number of studies. These CAPTCHAs rely on the distortion of text images rendering them unrecognizable to essentially pattern recognition...
In today's world of digital communication, as technology progresses, there is more and more attention required on image security. Many visual cryptography algorithms have been suggested and digital watermarking in association with visual cryptography is also proposed for more image security. An image watermarking model based on progressive visual cryptography is proposed to decide optimal number of...
In this work, we investigate the performance of different color spaces for watermarking purpose using quantization method through experimental analysis. We rely on imperceptibility and robustness as a measure of performance of a given color space and its different channels. Eight different color spaces are used in this work. The watermark is inserted into the LL3 subband for each channel of the color...
Person re-identification is one of the hot topics in computer vision. How to design a robust feature representation to identify pedestrians is a key problem for person re-identification. In this paper, a feature representation based on Multi-Statistics Cascade on Pyramid (MSCP) is proposed for person re-identification. The MSCP feature is composed of deep PCA network feature and hand-crafted features...
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