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Hardware-Based Acceleration of Image Filtration
Zelinka, Martin ; Slaný, Karel (referee) ; Vašíček, Zdeněk (advisor)
This bachelor's thesis deals with the hardware-based acceleration of image filtration using FIR filters. Define basic concept about digital image, describes the principle of filtration and briefly explains the techniques used to detect edges in an image and smoothing the image. The main aim of this work is the analysis of several acceleration methods of FIR filters, which are suitable for implementation in hardware, and the subsequent implementation of the selected method with the possibility of configuration changes at runtime with regard to the maximum throughput. In conclusion of this work it is described the evaluation of the method and made compared with the optimal software implementations.
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Image processing using Android device
Korchakov, Sergei ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master’s Thesis focuses on image processing on Android platform and development of an application, that is able to do face detection and recognition in real scene. Thesis gives highlight of modern algorithms of face detection. It first examines and compares the standard features of Android platform (FaceDetector a FaceDetectionListener) and JJIL, OpenIMAJ, OpenCV libraries experiment, and presents the results. For purposes of face recognition was selected OpenCV library. Three different algorithms of identification were tested: FisherFaces, EigenFaces a Local Binary Patterns Histograms. Based on performance comparison best methods were implemented in developed application.
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Hardware Acceleration of Image Filtering
Fiala, Martin ; Martínek, Tomáš (referee) ; Kořenek, Jan (advisor)
This master's thesis contains introduction to image filtration problems, especially to theoretical outlets, whose origin lies in linear systems theory and mathematical function analysis. There are described some approaches and methods which are used to image smoothing and for edge detection in an image. Mainly Sobel operator, Laplace operator and median filter are covered. The main contents of this project is discussion of some approaches of hardware acceleration of image filtering and design of time effective software and hardware implementations of filters in a form of program functions and combinational circuits using theoretical knowledges about time complexity of algorithms. Hardware and software implementation of named filters was done too. For every filter, time of filtration was measured and results were compared and analyzed.
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Hardware Acceleration of Image Filtering
Fiala, Martin ; Martínek, Tomáš (referee) ; Kořenek, Jan (advisor)
This master's thesis contains introduction to image filtration problems, especially to theoretical outlets, whose origin lies in linear systems theory and mathematical function analysis. There are described some approaches and methods which are used to image smoothing and for edge detection in an image. Mainly Sobel operator, Laplace operator and median filter are covered. The main contents of this project is discussion of some approaches of hardware acceleration of image filtering and design of time effective software and hardware implementations of filters in a form of program functions and combinational circuits using theoretical knowledges about time complexity of algorithms. Hardware and software implementation of named filters was done too. For every filter, time of filtration was measured and results were compared and analyzed.
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Image Denoising
Jurák, Martin ; Svoboda, Pavel (referee) ; Bařina, David (advisor)
Digital images are often corrupted by noise. Therefore, a lot of methods were designed for the purpose of denoising images. This paper describes and compares three of these methods: low-pass filters, bilateral filter and wavelet thresholding. Low-pass filters are linear filters applied on image by convolution. Their disadvantage is making images smooth. Bilateral filter is an extension of low-pass filters. It smooths images as well, however it preserves edges. Wavelet thresholding is a more complex method using wavelet transform for time-frequency representation of image whose coefficients are thresholded. The downside of this method is making artifacts in images. The PSNR and SSIM methods are used for measuring image quality.
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Hardware-Based Acceleration of Image Filtration
Zelinka, Martin ; Slaný, Karel (referee) ; Vašíček, Zdeněk (advisor)
This bachelor's thesis deals with the hardware-based acceleration of image filtration using FIR filters. Define basic concept about digital image, describes the principle of filtration and briefly explains the techniques used to detect edges in an image and smoothing the image. The main aim of this work is the analysis of several acceleration methods of FIR filters, which are suitable for implementation in hardware, and the subsequent implementation of the selected method with the possibility of configuration changes at runtime with regard to the maximum throughput. In conclusion of this work it is described the evaluation of the method and made compared with the optimal software implementations.
|
|
|
Image processing using Android device
Korchakov, Sergei ; Richter, Miloslav (referee) ; Honec, Peter (advisor)
This master’s Thesis focuses on image processing on Android platform and development of an application, that is able to do face detection and recognition in real scene. Thesis gives highlight of modern algorithms of face detection. It first examines and compares the standard features of Android platform (FaceDetector a FaceDetectionListener) and JJIL, OpenIMAJ, OpenCV libraries experiment, and presents the results. For purposes of face recognition was selected OpenCV library. Three different algorithms of identification were tested: FisherFaces, EigenFaces a Local Binary Patterns Histograms. Based on performance comparison best methods were implemented in developed application.
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