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This paper presents an acceleration method of the bilateral filter (BF) for multi-channel images. In most existing acceleration methods, the BF is approximated by an appropriate combination of convolutions. A major purpose under this framework is to achieve sufficient approximate accuracy by as few convolutions as possible. However, state-of-the-art methods for multi-channel images still requires...
This paper presents a scalable multiple GPU architecture for super multi-view (SMV) synthesis using the multi-view video plus depth (MVD) data. SMV synthesis is essential to generate 3D contents for the SMV 3D display with hundred views. SMV 3D display, recently released to support 108 viewpoints, shows the multiplexed result of small viewing interval. Hence, we should synthesize the intermediate...
During the last decade leukemia and lymphomas have been a hot topic in the biomedical area. Their diagnosis is a time-consuming task that, in many cases, delays treatments. On the other hand, discrete orthogonal moments (DOMs) are a tool recently introduced in biomedical image analysis. Here, we propose a combination of DOMs to help in the diagnosis of leukemia and lymphomas. We classify the IICBU2008-lymphoma...
Stereo matching methods estimate depth information of captured images. One way to estimate accurate depth values is to use the distance information. This method enhances the disparity map by preserving the edge region. In order to preserve the depth discontinuity near the edge region, it uses the distance information as a new weighting value for the matching cost function. However, this method has...
With the increasing availability of multi-view nonnegative data in practical applications, multi-view learning based on nonnegative matrix factorization (NMF) has attracted more and more attentions. However, previous works are either difficult to generate meaningful clustering results in terms of views with heterogeneous quality, or sensitive to noise. To address these problems, we propose a co-regularized...
One step in the image processing is filtering that located in the preprocessing. In the context of fetal analysis on the ultrasound image, filtering is really needed to enhance the quality of ultrasound image. This study conducted analysis of performance between Gaussian and bilateral filter in the fetal length. Peak signal to noise ratio (PSNR) was used to measure the quality of reconstruction the...
Person re-identification aims to match people across non-overlapping camera views. One of the challenges in re-identification is cross view matching, where the gallery and query data belong to different views. This problem is difficult because the person's appearance varies greatly due to significant viewpoint and poses changes. In this paper, we perform Kernel Canonical Correlation Analysis (KCCA)...
Object recognition on large-scale video has recently attracted considerable research interest due to the huge amount of data available on the Internet, surveillance systems, social media networks and autonomous vehicles. By representing large-scale videos as image sets, we can handle the complex data variations such as viewpoint, illumination, and pose. In this paper, we propose an efficient and robust...
Early detection of abnormality in image of skin is now considered the crucial contributor for successful treatment. We explored how constructing a sparse neighborhood net of pixels and distinction of patches in the image feature analysis play a role for diagnostic ability of lesion segmentation. Since image patches are considered like circumstance of many factors including skin tone, skin aberrations...
Recently, several effective features were proposed for person re-identification, such as Weight Histograms of Overlapping Stripes (WHOS) and Local Maximal Occurrence (LOMO), but it still need to explore new effective feature to improve the precision for person re-identification. So, in this paper, we proposed a new Dual Channel Gradient feature, which can be fused with WHOS and LOMO by directly concatenating...
In order to improve the docking success rate in Automated Aerial Refueling (AAR), it is important to identify the receiver aircraft's receptacle for boom receptacle refueling (BRR). Meanshift tracking algorithm only considers the H component color statistics of the target area, lacking spatial information, could easily lead to inaccurate tracking. Besides, Meanshift tracking algorithm could easily...
Glossoscopy is an important part of Traditional Chinese Medicine (TCM). To analyze the tongue properties objectively, we need extract the tongue region from images. This paper presents a method to segment the tongue images based on kernel FCM (Fuzzy Cluster means). Firstly we pre-processed the tongue images by gray-level integral projection. Secondly the features were extracted to form a feature vector...
Visualization of flow features, such as vortices, aids in analyzing complex unsteady (turbulent) flows and thus facilitate human cognition of flow phenomena. Typical data of unsteady flows are vector fields of velocity in four spatiotemporal dimensions (4D). Often empirical data of unsteady flows suffer from unknown measurement errors (i.e., undesired vectors). The undesired vectors lead to clutter...
Hybrid volume rendering algorithms combine techniques of different categories of volume visualization. Volume on Surface (VoS) is a hybrid volume rendering technique that maps volume information to isosurfaces, intending to accelerate the volume rendering process. In this paper, we introduce an improved version of the VoS technique. Furthermore, we conduct an evaluation of CUDA-based versions of both...
Tongue diagnosis is one of the main components of traditional Chinese medicine (TCM). Developing an objective and quantitative recognition model is very importantly and useful in the modernization of TCM. Currently, major problems in digital diagnoses of tongue images are extracting suitable features and building a high-performance classifier. To address these two issues, we present a robust approach...
Underwater images captured in a turbid medium often suffer from significant degradation of visibility. Conventional dehazing approaches focus on dehazing a single image by using multiple channels for color restoration and rarely consider computational efficiency. This paper proposes an online dehazing method with sparse depth priors using an incremental Gaussian Process (iGP). The main contribution...
An algorithm based on particle filters is employed to track moving objects in video streams from fixed and non-fixed cameras. Particle weighting is based on color histograms computed in the iHLS color space. Particle computations are parallelized with CUDA framework. The algorithm was tested on various GPU devices: a desktop GPU card, a mobile chipset and two embedded GPU platforms. The processing...
In areas of ecological interest, the detection and control of seaweed such as Posidonia Oceanica is usually performed by divers. Due to the limited capacity of the scuba tanks and the human security protocols, this task involves several short immersions leading to poor temporal and spatial data resolution. Thus, it is desirable to automate this task by means of underwater robots. This paper describes...
Most of current clustering methods are designed for general purpose other than a specific color pixel classification use. Color Line model representation emerged as the ultimate method for clustering pixels using RGB color components. However, this method is strongly sensitive to the adjustment of input parameters, which cannot conform to the frequent change of image structures and compositions. In...
Extracting meaningful structures and removing unimportant details or textures from a real world image is a classical problem in the domain of non-photorealistic rendering for images and benefits further computer vision related tasks as well. In this paper, we propose a structure sensitive bilateral filter by designing a novel weighting function which applies the second order variations of local color...
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