• Journal of the Korea Society of Computer and Information
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• v.4 no.1
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• pp.1-6
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• 1999

In this paper We propose the new lossless compression method which use Huffman Coding using the preprocessing to compress the still image. The proposed methode divide into two parts according to activity of the image. If activities are high, the original Huffman Coding method was used directly. IF activities are low, the nibble run-length coding and the bit dividing method was used. The experimental results show that compression rate of the proposed method was better than the general Huffman Coding method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.5
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• pp.990-995
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• 2010

Harris corner detector is commonly used to detect feature points for recognizing 2-D or 3-D objects. However, the feature points calculated from both of query and target objects need to be same positions to guarantee accurate recognitions. In order to check the positions of calculated feature points, we generate a Huffman tree which is based on adjacent feature values as inputs. However, the structures of two Huffman trees will be same as long as both of a query and targets have same feature values no matter how different their positions are. In this paper, we sort feature values and calculate the Euclidean distances of coordinates between two adjacent feature values. The Huffman Tree is generated with these Euclidean distances. As a result, the information of point locations can be included in the generated Huffman tree. This is the main strategy for accurate recognitions. We call this system as the HRM(Hybrid Retrieval Machine). This system works very well even when artificial random noises are added to original data. HRM can be used to recognize biological data such as proteins, and it will curtail the costs which are required to biological experiments.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1375-1378
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• 1987

In this paper, an efficient data compression algorithm for binary image is proposed. This algorithm makes use of the fact that boundaries contain all the information about such images. The compression efficiency is then further increased by efficient coding of Boundary Information Matrix. The comparison of performance with modified Huffman coding was made by a computer simulation with some images. The results of simulation showed that the proposed algorithm was more efficient than modified Huffman code.

• Proceedings of the KIEE Conference
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• 1993.11a
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• pp.346-349
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• 1993

A method for image compression based on decomposition is presented. We design the efficient coding technique for upper band image signals. This coding technique with directive 1-D DPCM is based on the statistical properties of upper bands. Lower band image signals is encoded using 2-D DPCM. The directive 1-D DPCM is performed, scanning upper bands according to edge direction. And then the predicted error signals of upper band sis coded using B1 and Huffman code, and the predicted error signals of lower band is coded using Huffman code. The proposed system shows improved performance when compared with other existing methods with respect to peak signal to noise ratio(PSMR) and human visual system(HVS) properties.

• Proceedings of the IEEK Conference
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• 2000.06c
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• pp.133-136
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• 2000

A RVLC(Reversible Variable Length Code) with an efficient table memory is proposed in this paper. In the conventional decoding methods, the weight of symbols and code values are used for the decoding table. These methods can be applied for Huffman decoding. In VLC decoding, many studies have been done for memory efficiency and decoding speed. We propose an improved table construction method for general VLC and RVLC decoding, which uses the transition number of bits within a symbol with an enhanced weight decomposition. In this method, tile table for RVLC decoding can be implemented with a smaller memory

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.1
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• pp.111-119
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• 1994

In this paper we propose a reversible image coding methods with progressive build-up function by bit-plane of multi-lavel image. Firstly, the differencial conversion is applied to reduce the entropy of source images. Then the bit-plane sequences of converted images are coded by means of the newly designed VFRL(Variable to Fixed Run-Llength) code and the RDHC(Run-length Dynamic Huffman Coding). We aim to the simple construction to reduce the complexity. The computer simulated results show that the proposed methods are very effective to the multi-level digital images. For "GIRL" and "COUPLE" of 1EEE monochromatic standard images, the compressibility are superior to the results obtained by the well-known universal codes.own universal codes.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 2004.11a
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• pp.213-213
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• 2004

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.11
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• pp.1-10
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• 1998

The advent of deep submicron technologies in the age of portable electronic systems creates a moving target for CAB algorithms, which now need to reduce power as well as delay and area in the existing design methodology. This paper presents a resynthesis algorithm for logic decomposition on mapped circuits. The existing algorithm uses a Huffman encoding, but does not consider glitches and effects on logic depth. The proposed algorithm is to generalize the Huffman encoding algorithm to minimize the switching activity of non-critical subcircuits and to preserve a given logic depth. We show how to obtain a transition-optimum binary tree decomposition for AND tree with zero gate delay. The algorithm is tested using SIS (logic synthesizer) and Level-Map (LUT-based FPGA lower power technology mapper) and shows 58%, 8% reductions on power consumptions, respectively.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.73-82
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• 2022

This paper shows the hiding process of unlimited secret text size in an image using three methods: the first method is the traditional method in steganography that based on the concealing the binary value of the text using the least significant bits method, the second method is a new method to hide the data in an image based on Exclusive OR process and the third one is a new method for hiding the binary data of the text into an image (that may be grayscale or RGB images) using Exclusive and Huffman Coding. The new methods shows the hiding process of unlimited text size (data) in an image. Peak Signal to Noise Ratio (PSNR) is applied in the research to simulate the results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2615-2628
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• 1997

In this paper, a new codebook design algorithm is proposed. It uses a DCT map based on two-dimensional discrete cosine of transform (2D DCT) and finite state vector quantizer (FSVQ) when the vector quantizer is designed for image transmission. We make the map by dividing input image according to edge quantity, then by the map, the significant features of training image are extracted by using the 2D DCT. A master codebook of FSVQ is generated by partitioning the training set using binary tree based on tree-structure. The state codebook is constructed from the master codebook, and then the index of input image is searched at not master codebook but state codebook. And, because the coding of index is important part for high speed digital transmission, it converts fixed length codes to variable length codes in terms of entropy coding rule. The huffman coding assigns transmission codes to codes of codebook. This paper proposes single-side growing huffman tree to speed up huffman code generation process of huffman tree. Compared with the pairwise nearest neighbor (PNN) and classified VQ (CVQ) algorithm, about Einstein and Bridge image, the new algorithm shows better picture quality with 2.04 dB and 2.48 dB differences as to PNN, 1.75 dB and 0.99 dB differences as to CVQ respectively.