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.
Global warming induced drastic climate changes have increased the frequency of natural disasters such as flooding, worldwide. Flooding is a constant threat to humanity and reliable systems for flood monitoring and ana...
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ISBN:
(纸本)9781509006137
Global warming induced drastic climate changes have increased the frequency of natural disasters such as flooding, worldwide. Flooding is a constant threat to humanity and reliable systems for flood monitoring and analysis need to be developed. Flood hazard assessment needs to take into account physical characteristics such as flood depth, flow velocity and the duration of flooding. This paper provides the researchers with a detailed compilation of the methods that can be used for the estimation of flood water depth. A comparative study has been done between the water depth estimation techniques based on imageprocessing and those which does not involve imageprocessing. The comparison is based on various attributes such as implementation methods, advantages, accuracy and cost. imageprocessing methods are classified based on various algorithms such as character recognition, feature extraction, region of interest (ROI), FIR filter etc. Similarly, non-imageprocessing methods are classified based on hardware used such as sensors, level indicators, etc., and other signal based techniques. This study can be used to identify the best method for flood water depth estimation.
This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper propose...
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ISBN:
(纸本)9781509041060
This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper proposes a fingerprint recognition technique based on wavelet-based texture pattern recognition method. By collecting incomplete fingerprints of 2 people with 6 images each. The original seven of uncompleted fingerprint images were undetected and only one was detected. After enhancing image quality using wavelet transform method, it was found that those of seven images were completed. The comparison method was a matching technique. This work focuses on the ability of the program and knowledge of imageprocessing by studying algorithms of imageprocessing. In design algorithm process, different technique enhancements were employed as well as the study of different of filters and algorithms based on existing research results from literature.
Clouds can obscure ground information during remote sensing imaging. Cloud removal technology for a single image becomes significant when no images containing cloud-free regions are available. After the fundamental pr...
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ISBN:
(纸本)9781509009428
Clouds can obscure ground information during remote sensing imaging. Cloud removal technology for a single image becomes significant when no images containing cloud-free regions are available. After the fundamental principle of dual tree complex wavelet transform (DTCWT) was reviewed, and the frequency relationships between clouds and ground objects in remote sensing images were analyzed, a novel algorithm to remove clouds from a single remote sensing image was proposed. The algorithm divided the cloud-contaminated image into low level high frequency sub-bands, high level high frequency sub-bands and low frequency sub-band by DTCWT. The low level high frequency sub-bands were filtered to enhance the ground object information by Laplacian filtering. The other two types of sub-bands were processed to remove cloud by applying the method of cloud layer coefficient weighting (CLCW). imageprocessing experiments were implemented. Their results were analyzed. It proved the Laplacian contributes to enhancing ground object information adaptively. CLCW has the ability to remove clouds while preserving the ground object information outside the cloud cover. The proposed algorithm is greatly superior to algorithms based on traditional wavelet transform and the wavelet threshold theory.
In the early years of college, students have the need to learn how to program in any programming language. It is important to see the differences between programming languages and their rules. We are proposing an inte...
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ISBN:
(纸本)9781509023349
In the early years of college, students have the need to learn how to program in any programming language. It is important to see the differences between programming languages and their rules. We are proposing an interactive and self-study system for students to acquire the knowledge they need, from data structures to algorithms using multiple programming languages. The system gives the students some exercises that outputs an image. The student's image will be compared with the correct image that is in the system and the system judges the student's image will is correct or not. The students will program the exercises in the selected programming languages. Eventually the system will help students learn multiple programming languages, especially, how to solve problems regardless of programming language.
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super-resolution algor...
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ISBN:
(纸本)9781467399623
Increasing spatial resolution is often required in many applications such as entertainment systems or video surveillance. Apart from using higher resolution sensors, it is also possible to apply super-resolution algorithms to realize an increased resolution. Those methods can be divided into approaches that rely on only a single low resolution image or on multiple low resolution video frames. While incorporating more frames into the super-resolution is beneficial for the resolution enhancement in principle, it is also likely to introduce more artifacts from inaccurate motion estimation. To alleviate this problem, various weightings have been proposed in the literature. In this paper, we propose an extended dual weighting scheme for an interpolation-based super-resolution method based on Voronoi tessellation that relies on both a motion confidence weight and a distance weight. Compared to non-weighted super-resolution, the proposed method yields an average gain in luminance PSNR of up to 1.29 dB and 0.61 dB for upscaling factors of 2 and 4, respectively. Visual comparisons substantiate the objective results.
In this research, a matrix notation method to extract discrete orthogonal Racah moments is proposed to reduce the computation time. To verify this new computational method, the image reconstructions from higher orders...
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ISBN:
(纸本)9781467387224
In this research, a matrix notation method to extract discrete orthogonal Racah moments is proposed to reduce the computation time. To verify this new computational method, the image reconstructions from higher orders of Racah moments are performed. Our experimental results show that the Racah moments computing time has been reduced tremendously, while the testing image can be reconstructed completely by Racah moments of orders up to 510 without any error.
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