• Journal of the Optical Society of Korea
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• v.20 no.5
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• pp.586-592
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• 2016

This paper proposes a luminance compensation method using optical sensors to achieve high luminance uniformity of active matrix organic light-emitting diode (AMOLED) displays. The proposed method compensates for the non-uniformity of luminance by capturing the luminance of entire pixels and extracting the characteristic parameters. Data modulation using the extracted characteristic parameters is performed to improve luminance uniformity. In addition, memory size is optimized by selecting an optimal bit depth of the extracted characteristic parameters according to the trade-off between the required memory size and luminance uniformity. To verify the proposed compensation method with the optimized memory size, a 40-inch 1920×1080 AMOLED display with a target maximum luminance of 350 cd/m² is used. The proposed compensation method considering a 4σ range of luminance reduces luminance error from ± 38.64%, ± 36.32%, and ± 43.12% to ± 2.68%, ± 2.64%, and ± 2.76% for red, green, and blue colors, respectively. The optimal bit depth of each characteristic parameter is 6-bit and the total required memory size to achieve high luminance uniformity is 74.6 Mbits.

• Journal of KIISE:Computer Systems and Theory
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• v.31 no.5_6
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• pp.321-327
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• 2004

SPIHT algorithm is a wavelet based fast and effective technique for image compression. It uses a list structure to store status information which is generated during set-partitioning of toro-tree. Usually, this requires lots of additional memory depending on how high the bit-rate is. Therefore, in this paper, we propose a new technique called MZC-BFS, which needs no additional memory when running SPIHT algorithm. It explicitly performs a breadth first search of the spatial-tree using peano-code and eliminates additional memory as it uses pre-status significant test for encoding and LSB bits of some coefficients for decoding respectively. This method yields nearly the same performance as SPIHT. This may be desirable in fast and simple hardware implementation and reduces the cost of production because no lists and additional memory are required.

• Journal of the Korean Institute of Navigation
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• v.19 no.3
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• pp.21-28
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• 1995

Mathematical morphology skeleton image processing makes many partial skeleton image planes from an original binary image. And the original binary image can be reconstructed without any distortion by summing the first partial skeleton image plane and each dilated partial skeleton image planes using the same structuring element. Especially compression effects of Elias coding to the morphological globally minimal skeleton(GMS) image, is better than that of PCX and Huffman coding. And then this paper proposes mathematical morphological GMS image processing which can be applied to a binary image transmitting for facimile and big size(bigger than $64{\times}64$ size) bitmap fonts storing in a memory.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1508-1515
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• 2017

This paper proposes the defect detection method for automatic inspection machines in printed circuit boards (PCBs) manufacturing system. The defects of PCB such as open, short, pin hole and scratch can be detected by comparing the standard image and the target image. The standard image is obtained from CAD file such as ODB++ format, and the target image is obtained by arranging, filtering and binarization of captured PCB image. Since the PCB size is too large and image resolution is too high, the image processing requires a lot of memory and computational time. The wavelet transform is applied to compress the standard and target images, which results in reducing the memory and computational time. To increase the inspection accuracy, we utilize the he HH-domain as well as LL-domain of the transformed images. Experimental results are finally presented to show the performance improvement of the proposed method.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.308-320
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• 2021

Conventional image quality studies have been focused on 'naturalness' and has relied on memory color. Memory colors are mainly formed for familiar objects with prior experience, and the more faithfully these memories are reflected, the more naturalness of the reproduced image quality increases. In particular, the brightness and saturation of memory colors play an important role in increasing the preference of image quality as well as naturalness. Therefore, in the case of existing image quality studies, image quality characteristics were studied focusing on natural objects and people with memory. We extracted representative images of each genre (sports, documentaries, news, entertainment and music, and movies), adjusted the brightness, contrast, and saturation of each image, and conducted an experiment to evaluate perceived quality. Based on situational context, the results of this classification indicated that genres of television content can be divided into two categories: proximate and indirect experiences. Proximate experience best characterizes outdoor sports, dramas, and nature documentaries, where their image qualities have shown to have a strong correlation with brightness and contrast. On the other hand, indirect experience best characterizes news, music shows and SF/action movies. The image quality perception for indirect experiences was shown to be closely related to and optimized by contrast and saturation.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.513-516
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• 2003

Current paper introduces the additional multimedia module for digital TV. The module is developed for displaying the image captured by digital still camera, camcorder, or PC in the digital TV. For these purpose, the module has the interface circuit for accessing five media type of memory cards. It decodes JPEG, BMP, or TIFF image data saved in the memory card and converts the image data to analog RGB signal. It also supports three types of output image size from HD to WXGA resolution. So the introduced module could be adopted In the most of digital TV.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2019.06a
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• pp.98-101
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• 2019

At present, deep convolutional neural networks have made a very important contribution in single-image super-resolution. Through the learning of the neural networks, the features of input images are transformed and combined to establish a nonlinear mapping of low-resolution images to high-resolution images. Some previous methods are difficult to train and take up a lot of memory. In this paper, we proposed a simple and compact deep recursive residual network learning the features for single image super resolution. Global residual learning and local residual learning are used to reduce the problems of training deep neural networks. And the recursive structure controls the number of parameters to save memory. Experimental results show that the proposed method improved image qualities that occur in previous methods.

• JSTS:Journal of Semiconductor Technology and Science
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• v.17 no.3
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• pp.473-482
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• 2017

Hand gesture recognition is regarded as new Human Computer Interaction (HCI) technologies for the next generation of mobile devices. Previous hand gesture implementation requires a large memory and computation power for hand segmentation, which fails to give real-time interaction with mobile devices to users. Therefore, in this paper, we presents a low latency and memory-efficient hand segmentation architecture for natural hand gesture recognition. To obtain both high memory-efficiency and low latency, we propose a streaming hand contour tracing unit and a fast contour filling unit. As a result, it achieves 7.14 ms latency with only 34.8 KB on-chip memory, which are 1.65 times less latency and 1.68 times less on-chip memory, respectively, compare to the best-in-class.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.360-363
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• 1999

Video data compression is a major key technology in the field of multimedia applications. Variable-length coding is the most popular data compression technique which has been used in many data compression standards, such as JPEG, MPEG and image data compression standards, etc. In this paper, we present memory efficient VLC decoder architecture for MPEG-2 application which can achieve small memory space and higher throughput. To reduce the memory size, we propose a new grouping, remainder generation method and merged lookup table (LUT) for variable length decoders (VLD's). In the MPEG-2, the discrete cosine transform (DCT) coefficient table zero and one are mapped onto one memory whose space requirement has been minimized by using efficient memory mapping strategy The proposed memory size is only 256 words in spite of mapping two DCT coefficient tables.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.147-157
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• 2011

Webcam doesn't perform memory-alignment in order to reduce the transmission time of image data. Memory-unaligned image data is unsuitable for the processing on GPU. Accordingly, we convert it to available color format for optimization in high speed image processing. In this paper, we propose a technique that accelerates webcam's color format conversion by using NVDIA CUDA. We propose an optimization which is about memory accesses and thread composition, also evaluate memory and computing performance for verifying a hypothesis which is the performance of the proposed architecture and optimizing degree on low-performance GPU. Following the optimization technique, we show performance improvements over maximum 68 percent.