2.06 Vincent Mary School of Engineering
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Item15 ทีมรถจักรยานหุ่นยนต์ไร้คนบังคับ ผ่านเข้าสู่รอบชิงแชมป์ประเทศไทย( 2012)ทีมนักศึกษาคณะวิศวกรรมศาสตร์ มหาวิทยาลัยอัสสัมชัญ (ทีมยู้ฮู ยู้ฮู) ได้ผ่านการคัดเลือก 15 ทีมสุดท้ายโดยได้รับรางวัล 20,000 บาท สำหรับนำไปพัฒนาประสิทธิภาพของรถจักรยานหุ่นยนต์เพื่อเข้าแข่งขันรอบชิงชนะเลิศ ในการแข่งขันจักรยานหุ่นยนต์ชิงแชมป์ประเทศไทย ครั้งท่ี 2 จัดโดยบริษัทซีเกทเทคโนโลยี (ประเทศไทย) จำกัด
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Item4x4 High-Magnification Image Reconstruction Based on Hybrid of Multi-frame SR Approach and Image Super Resolve Algorithm( 2015-11) Vorapoj PatanavijitFrom tremendously soliciting high quality and high resolution images, sundry image reconstruction algorithms have been researched and implemented during the last fifteen years, especially for high-magnification image reconstructions. In this paper, we develop high-magnification image reconstruction based on hybrid of a multi-frame SR approach and an image super resolve algorithm for 4x4 magnifying in resolution. First, a group of polluted low resolution images are amalgamated for 2x2 magnifying in resolution and suppressing the noise in each polluted low resolution images. Next, the 2x2 magnified image is reconstructed by using image super resolve algorithm based on the high-frequency image prediction to be the 4x4 magnified image. In the performance testing section, the outcomes on both benchmark (in PSNR) and virtual quality, contrasting with previous classical algorithms from the research literature (such as a classical interpolation technique, a classical SRR and an image super resolve algorithm), expose that the proposed hybrid framework has the better performance in both benchmark (in PSNR) and virtual quality.
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ItemActual benefits of connecting to the internet(Assumption University, 1995) Anucha Pitaksanonkul ; Assumption University. Vincent Mary School of Engineering
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ItemAn Adaptive And Statistical Efficiency Myriad Filter For A Recursive Image Reconstruction Using a Multi-Frame SRR Algorithm With A Stochastic Regularization For Video Sequences( 2015) Vorapoj PatanavijitIn real applied implementations, a collection of classical linear filtering theories, for example, a Median filter and a Mean filter, can be only applied to the Gaussian noise environments due to the fact that these linear filters usually gives the poor performance under the presence of non-Gaussian noise environments. Because of the motion estimation blunder and observation process error, which are usually caused from real electronic noise, non-accurate optical devices or mathematical simplification models of observed process systems, the SRR (Super Resolution Reconstruction) algorithms using classical linear filters (a Median filter and a Mean filter) should possibly demote the quality of a reconstructed image rather than improve its quality. Under non-Gaussian environments, a class of flexible filters with high statistical efficiency, so called Myriad filter, has been proposed and its solid theoretical principle was analyzed for indicating that the Myriad filter is usually more powerful than a class of linear filters, especially for non-Gaussian environments. This paper proposes an adaptive and statistical efficiency myriad filter for a recursive image reconstruction for applied implementing on real video sequences, which are contaminated by both Gaussian and non-Gaussian noise environments. Thus, the Myriad filter, which is implemented for getting rid of noise in an expected image and for valuing the contrast between the back-propagated expecting of the reconstructed high resolution image and a group of low resolution images, is involved in this stochastic regularization SRR framework for the elimination proposing of Gaussian and non-Gaussian noise. Because of an ill-pose condition of the SRR algorithm, Tikhonov regularization methodology is mathematically required for getting rid of deformation from the reconstructed high resolution image and reforming the calculated time of its convergence. Under a lot of noisy corrupted environments (Noiseless, AWGN, Impulsive Noise, Poisson Noise and Speckle Noise at unequal noise power), the performance from the both PSNR and virtual quality prospect of the proposed SRR algorithm using Myriad filter, which is compared with SRR algorithms using classical linear filters (a Median filter and a Mean filter) are depicted and the proposed SRR algorithm gives the superior visually quality and, thus, superior PSNR than the SRR algorithms using classical linear filters.
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ItemAdvance magnetic card access control(Assumption University, ) Pinet Cherdhirunkorn ; Nontryee Smithinunt, jt. auth.
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ItemAlpha & numeric led displayer(Assumption University, ) Huang, Sheng-Ho ; Akranit S., jt. auth.
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ItemAn Alternative Technique using Median Filter for Image Reconstruction based on Partition Weighted Sum Filter( 2016-06) Vorapoj PatanavijitIn this paper, we propose an alternative technique for image reconstruction which it is combined existing methods for better performance in spatial domain using the median (MED) filter based on partition weighted sum (PWS) filter. Four noise models are considered including additive white Gaussian noise (AWGN), poission noise (PN), salt and pepper noise (SPN) and speckle noise (SN) under different image types such as aerial image, face image, scenic image, and text image. The simulation results show that the median based partition weighted sum (MPWS) filter provides better results than the MED and PWS filters in case of AWGN and SPN when the noise probability is not less than 20% for all image types. However, this filter takes longer average simulation time than the MED and PWS filters.
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