The edge detection is one of the key techniques in most imageprocessing applications. The canny edge detection is proven to be able to significantly outperform existing edge detection techniques due to its superior p...
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The edge detection is one of the key techniques in most imageprocessing applications. The canny edge detection is proven to be able to significantly outperform existing edge detection techniques due to its superior performance. Unfortunately, the implementation of the systems in real-time is computationally complex, high hardware cost with increased latency. The proposed canny edge detection algorithm uses approximation methods to replace the complex operations, the pipelining is employed to reduce the latency. Finally, this algorithm is implemented on Xilinx Virtex-5 FPGA. When compared with the previous hardware architecture for canny edge detection, the proposed architecture requires fewer hardware costs and takes 1ms to detect the edges of 512×512 image.
Segmentation is a process to obtain the desirable features in imageprocessing. However, the existing techniques that use the multilevel thresholding method in image segmentation are computationally demanding due to t...
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ISBN:
(纸本)9781467378086
Segmentation is a process to obtain the desirable features in imageprocessing. However, the existing techniques that use the multilevel thresholding method in image segmentation are computationally demanding due to the lack of an automatic parameter selection process. This paper proposes an automatic parameter selection technique called an automatic multilevel thresholding algorithm using stratified sampling and Tabu Search (AMTSSTS) to remedy the limitations. It automatically determines the appropriate threshold number and values by (1) dividing an image into even strata (blocks) to extract samples; (2) applying a Tabu Search-based optimization technique on these samples to maximize the ratios of their means and variances; (3)preliminarily determining the threshold number and values based on the optimized samples; and (4) further optimizing these samples using a novel local criterion function that combines with the property of local continuity of an image. Experiments on Berkeley datasets show that AMTSSTS is an efficient and effective technique which can provide smoother results than several developed methods in recent years.
Many computer role-playing games that mime a science fiction or fantastic world have a static world map or the map changes under some scripted assumptions that hardly reproduce the dynamic of a play. In this paper I p...
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ISBN:
(纸本)9781509041251
Many computer role-playing games that mime a science fiction or fantastic world have a static world map or the map changes under some scripted assumptions that hardly reproduce the dynamic of a play. In this paper I propose a novel algorithm that enables real time terrain calculation even on a very large world map. An algorithm uses approach based on attraction force calculation and uses gradient methods combined with fast approximation of Gaussian filter and fast implementation of median filtration. With such an approach it is possible to fast adapt and rebuild the virtual world taking into account every nuance that happened during play. Due to this a player has the feeling of control and influence of his or her deeds to overall game which is very important aspect of every role-playing scenario. Because single iteration of an algorithm last about 176.01 ± 12.57 milliseconds (in frequency nearly 6 Hz for large 256×256 grids) the resulting map might be adjusted dynamically during game and a player might be aware of it. This size of a grid is sufficient for simulation very large virtual world that typically appears in role-playing games.
The huge growth in the smartphones market has led to the improvement in ARM architectures, so that today there are many devices based on them, with sufficient capacity to deal with certain imageprocessing application...
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ISBN:
(纸本)9781509013159
The huge growth in the smartphones market has led to the improvement in ARM architectures, so that today there are many devices based on them, with sufficient capacity to deal with certain imageprocessing applications. These are used in VSN (Visual Sensor Networks) and in other scenarios, where the energy used in the process is a parameter to be considered. In these scenarios, and with the HMP (Heterogeneous multi-processing) architectures on which the current platforms are based, it is necessary to determine both the core as well as the working frequency in order to achieve the application's imageprocessing objectives with the least possible energy consumption. In this type of system, the workload is oriented towards interactive applications, so the priorities are different to those of VSN type systems. Conventional regulation algorithms do not make appropriate use of the processor's frequency range, in relation to the load. This paper analyses the influence of the maximum frequency value on system performance and power consumption.
With the progressive development of the computer-aided diagnosis (CAD) systems, analysis of high resolution histopathological images has become more easier. In the proposed study, the effects of different color spaces...
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With the progressive development of the computer-aided diagnosis (CAD) systems, analysis of high resolution histopathological images has become more easier. In the proposed study, the effects of different color spaces used in various studies in the literature are investigated for the discrimination of cellular structures from background in histopathological images. For this purpose, performances of k-means, fuzzy c-means and expectation-maximization algorithms are compared in different color spaces. In the experimental results section, different segmentation accuracy metrics are presented in comparative manner.
The latest advancement in imaging applications has increased the need for more High Definition Range (HDR) imaging, which is not easily attainable by common imaging sensors. However, the use of multiple exposure image...
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ISBN:
(纸本)9781509018185
The latest advancement in imaging applications has increased the need for more High Definition Range (HDR) imaging, which is not easily attainable by common imaging sensors. However, the use of multiple exposure images, that cover multiple exposure settings for the captured scene, and their combination in a single image via image fusion has been proposed in the literature and seems a viable solution. In this paper, the authors combine two image fusion methods to perform multiple exposure fusion. They use Mitianoudis and Stathaki [1] method to fuse the luminance channel and the Mertens et al [2] method to fuse the color channels. The derived fusion output outperforms both individual methods and other state-of-the-art methods.
Due to the wide applicability of pedestrian detection in surveillance and safety, this research topic has received much attention in computer vision literature. However, the focus of this research mainly lies in detec...
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ISBN:
(纸本)9781467389112
Due to the wide applicability of pedestrian detection in surveillance and safety, this research topic has received much attention in computer vision literature. However, the focus of this research mainly lies in detecting and locating pedestrians individually as accurate as possible. In recent years, a number of datasets are captured using a forward looking camera from a car, which imposes the application of warning the driver when pedestrians are in front of the car. For such applications, it is not required to detect each pedestrian independently, but to generate an alarm when necessary. In this paper we explore techniques to boost the accuracy of recent channel-based algorithms in this application: algorithmic refinements as well as the inclusion of an LWIR image channel. We use the KAIST dataset which is constructed from image-pairs of both the visual and the LWIR spectrum, in day and night conditions. We study the influence of techniques that have shown success in literature.
This paper focuses on the problem of image registration, which is a fundamental and important problem in computer vision. As local features are effective to tackle the task of image registration, hence, we exploit SIF...
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ISBN:
(纸本)9781509055319
This paper focuses on the problem of image registration, which is a fundamental and important problem in computer vision. As local features are effective to tackle the task of image registration, hence, we exploit SIFT feature descriptors to describe the interesting key points in images. The reasons is that SIFT can extract features which are invariant to scaling, orientation, affine transforms and illumination changes. Afterwards, to lower the effects of outliers, the nearest distance ratio method is used to get initial matched feature descriptor pairs, and then scale-orientation joint restriction is used to detect false matching SIFT descriptor pairs. After using Random Sample Consensus to prune outliers, image registration results can be obtained. In the end, we develop an experiment based on QuickBird and IKONOS datasets, and very positive results are achieved.
In the last decades, there have been a decline in ecosystems natural resources. The objective of the thesis is to develop advanced imageprocessing techniques applied to high resolution remote sensing imagery for the ...
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ISBN:
(纸本)9781509012268
In the last decades, there have been a decline in ecosystems natural resources. The objective of the thesis is to develop advanced imageprocessing techniques applied to high resolution remote sensing imagery for the ecosystem conservation. Different pre-processing steps have been applied in order to acquire high quality imagery. The thesis is focused in three ecosystems from Canary Islands where, after an extensive analysis and evaluation, Weighted Wavelet `à trous' through Fractal Dimension Maps and Fast Intensity Hue Saturation are used in the pansharpening process, then, a RPC model performs the orthorectification and finally, the atmospheric correction is carried out by the 6S algorithm. The final step is to generate marine and terrestrial thematic products using advanced classification techniques for the management of natural resources.
The Mojette transform has found several applications to this date. Some of them, such as systems for distributed file storage, or digital tomography systems exploit one of the main properties of Mojette transform - re...
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ISBN:
(纸本)9781509016754
The Mojette transform has found several applications to this date. Some of them, such as systems for distributed file storage, or digital tomography systems exploit one of the main properties of Mojette transform - redundancy. However, sometimes this feature is not desirable. This is a case of applying Mojette transform for image encoding, or decoding. In these applications, higher rate of redundancy can cause longer processing times and bigger size of image data. These problems can be solved by group of procedures, which would work in a determined manner. In this article, we tried to propose a set of algorithms, which would reduce the drawbacks of Mojette transform, but exploit its advantages in the field of image coding.
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