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Efficient solutions must be considered, in order to solve the problem of intensive computing of the image processing applications and to achieve high real-time performance. The graphics processing unit (GPU) is an effective and the most recent method used for accelerating extensive calculation algorithms to reduce the execution time by exploiting the power of parallel programming techniques and to...
This paper proposes the parallel implementation of finite volume method based on weighted average flux (WAF) to solve the shallow water equations on a graphic processing unit. We develop two parallel programs which are 1-dimension thread block and 2-dimension thread block, respectively. We compare the performance of these two versions with a sequential program. The numerical experiment is performed...
Image filtering is a process of reducing noise which degrades the performance of image processing. In some applications such as segmentation or classification, denoising has been designed to smooth the homogeneous areas while keeping and enhancing the edges. In several applications such as video analysis, image-guided surgical interventions or visual servoing, real-time denoising is needed. The devoted...
Edge detection is one of the most important paradigm of Image processing. Images contain millions of pixel and each pixel information is independent of its neighbouring pixel. Hence this paper puts to test the capability of Graphics Processing Unit (GPU) to compute in parallel against the millions of pixel calculations involved in image processing. Each pixel operation is independent from other thus...
Graphics Processing Units (GPUs) are used today as affordable energy-efficient method of acceleration for computationally exhaustive algorithms to decrease execution time exploiting the power of parallel programing techniques. In the field of medical imaging, GPUs became crucial acceleration method for computationally exhaustive algorithms. This paper presented the effect of memory optimization on...
Intuitionistic fuzzy edge detection algorithm has been used for the signification or characterization of images. It has been designed by experts and the algorithm provides to aim to minimize errors. However, it has a fixed value for thresholding. In this paper, a hybrid algorithm has been developed using the Otsu method which is calculated a threshold value depending on the images. To be applicable...
This paper introduces the smoke detection method for surveillance cameras. The background subtraction was used to determine moving objects. Color probability was utilized to find possible smoke pixels in a scene. Separate pixels, acquired by background subtraction, were united by morphological operations and connected components labeling methods. The existence of the smoke region is then confirmed...
For autonomous navigation the real-time processing is crucial. This paper proposes a method to detect the lane markings in real-time using the advantage of parallel processing. A region of interest is constrained by the current velocity of a vehicle. The segmentation was achieved by utilizing a difference in color between lane marking and road pavement. The overall process is divided into three steps...
Parallel programming has been extensively applied to different fields, such as medicine, security, and image processing. This paper focuses on parallelizing the Laplacian filter, an edge detection algorithm, using CUDA. We have conducted a performance analysis to benchmark the sequential Laplacian version against the CUDA parallel approach. Results show that the parallelization of Laplacian filter...
In this paper propose a GPU-based parallel processing method for real-time image segmentation with neural oscillator network. Range image segmentation methods can be divided into two categories: edge-based and region-based. Edge-base method is sensitive to noise and region-based method is hard to extracting the boundary detail between the object. However, by using LEGION (Locally Excitatory Globally...
This paper proposes an efficient GPU-based massively parallel implementation of the edge-directed adaptive intra-field deinterlacing method which interpolates the missing pixels based on the deinterlaced covariance estimated from the interlaced covariance according to the geometric duality between the interlaced and the deinterlaced covariance. Although the edge-directed adaptive intra-field deinterlacing...
Most image processing algorithms are inherently parallel, so multithreading processors are suitable in such applications. In huge image databases, image processing takes very long time for run on a single core processor because of single thread execution of algorithms. GPU is more common in most image processing applications due to multithread execution of algorithms, programmability and low cost...
In many application fields, an appropriate high-quality fast image up sampling method is required. Although many interpolation-based up sampling methods have been proposed, the quality of result images is not satisfactory. Some of them are very fast, but produce poor quality images, the others can produce high quality images, but the methods in them are slow. In our paper, we proposed a fast statistical...
In order to solve the parallel processing problem of mass data, stream processor develops quickly in recent years. The essence of stream processor is getting high performance according to executing thousands of threads parallelly. It is widely used in scientific computing, data mining, video quality analysis and other fields. But mass threads means the high costs of thread synchronization. Mass computing...
This paper design and implement a parallel fast trilateral filter algorithm on GPU. The trilateral filter can be decomposed into two bilateral filters which are implemented by the parallelized bilateral filter on CUDA separately. The performance optimization strategies are intensively discussed. The occupancy of CUDA kernel for trilateral filter reaches 0.833 which is measured by Visual Profiler....
An image acquisition and processing system to measure the width and inspect the quality of the stainless steel strip in a production line is presented in this paper. It is based on the real-time processing of the images acquired by a twin linear camera system. Image processing algorithms to detect defects and anomalies in the edges have been implemented. The core of the image processing is submitted...
Medical imaging techniques such as X-ray, Ultrasound, CT and MRI scan are widely used for diagnosis. The 2D medical images from these scans are difficult to interpret because they can only show cross section views of a human body. Interpreting these images requires experts or trained professionals. Reconstructing 2D images into 3D models can help with the interpretation process. However, such model...
The retinex algorithm is commonly used to image enhancement. Recently, the image size what we usually use, is bigger and bigger. The digital camera use big size images and the television is change to HD television. So the image enhancement time is longer and longer and it needs more powerful system such as multi-core, many-core systems. But these multi-core, many-core systems or powerful systems are...
The segmentation of cervical vertebra in X-Ray radiographs can give valuable information for the study of the vertebral mobility. One particular characteristic of the X-Ray images is that they present very low grey level variation and makes the segmentation difficult to perform. In this paper, we propose a segmentation procedure based on the Active Shape Model to deal with this issue. However, this...
In view of the limitations of classic differential operators and the defects of traditional Gabor wavelet transform algorithm for edge detection, we present a parallel Gabor wavelet transform method for edge detection based on CUDA in this paper. Firstly we introduce the wavelet transform algorithm, and then discusse the feasibility that parallel detect edge in wavelet transform and relize it,the...
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