• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.335-344
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• 2014

As a kind of 2D spatial coordinate transform, image warping is a basic image processing technique utilized in various applications. Though image warping algorithm is composed of relatively simple operations such as memory accesses and computations of weighted average, real-time implementations on embedded vision systems suffer from limited computational power because the simple operations are iterated as many times as the number of pixels. This paper presents a real-time implementation of a look-up table(LUT)-based image warping using an FPGA. In order to ensure sufficient data transfer rate from memories storing mapping LUT and image data, appropriate memory devices are selected by analyzing memory access patterns in an LUT-based image warping using backward mapping. In addition, hardware structure of a parallel and pipelined architecture is proposed for fast computation of bilinear interpolation using fixed-point operations. Accuracy of the implemented hardware is verified using a synthesized test image, and an application to real-time lens distortion correction is exemplified.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.233-237
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• 2009

This paper represents a new approach which addresses quality degradation of a synthesized view, when a virtual camera moves forward. Generally, interpolation technique using only two neighboring views is used when a virtual view is synthesized. Because a size of the object increases when the virtual camera moves forward, most methods solved this by interpolation in order to synthesize a virtual view. However, as it generates a degraded view such as blurred images, we prevent a synthesized view from being blurred by using more cameras in multiview camera configuration. That is, we solve this by applying super-resolution concept which reconstructs a high resolution image from several low resolution images. Therefore, data fusion is executed by geometric warping using a disparity of the multiple images followed by deblur operation. Experimental results show that the image quality can further be improved by reducing blur in comparison with interpolation method.

• The Journal of the Korea Contents Association
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• v.2 no.2
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• pp.27-35
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• 2002

This paper describes the implementation of cosmetic surgery simulation system by means of the bilinear warping and interpolation using a pair of control points in order to get the information which can be used to compare the before and the after the surgery. If an user provides a pair of control points, first of all, the system determines warping egion using the points and divides the whole region into four subregions which includes the control points as a corner ones. Then, for each subregion, it calculates warping coefficients for backward mapping using the four known comer points of each subregion. Using those calculated coefficients, the system gets the corresponding position of each pixel on the subregion of original image which matches the subregion of resulting image. Finally, a new pixel value is calculated by bilinear interpolation using the closest four pixel values of the position. The same process is applied to the remaining subregions. Through the experiments, we could find natural aesthetic results without any side effects which unnatural aesthetic results without any side effects which unnaturally distort the boundary of warping region.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.351-359
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• 1991

This paper describes performances of speaker adaptation using a probabilistic spectral mapping matrix in hidden-Markov model(HMM) -based Korean isolated word recognition. Speaker adaptation based on probabilistic spectral mapping uses a well-trained prototype HMM's and is carried out by Viterbi, dynamic time warping, and forward-backward algorithms. Among these algorithms, the best performance is obtained by using the Viterbi approach together with codebook adaptation whose improvement for isolated word recognition accuracy is 42.6-68.8 %. Also, the selection of the initial values of the matrix and the normalization in computing the matrix affects the recognition accuracy.