• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.175-177
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• 2018

This paper proposes an algorithm to speed up block structure partition of quad tree plus binary tree (QTBT) in Joint Exploration Test Model (JEM) encoder. The proposed fast encoding of QTBT block partition employs three spatially neighbor coded blocks, such as left, top-left, and top of current block, to early terminate QTBT block structure pruning. The propose algorithm is organized based on statistical similarity of those spatially neighboring blocks, such as block depths and coded block types, which are coded with overlapped block motion compensation (OBMC) and adaptive multi transform (AMT). The experimental results demonstrate about 30% encoding time reduction with 1.3% BD-rate loss on average compared to the anchor JEM-7.1 software under random access configuration.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5B
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• pp.285-295
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• 2008

Internet routers perform packet forwarding which determines a next hop for each incoming packet using the packet's destination IP address. IP address lookup becomes one of the major challenges because it should be performed in wire-speed for every incoming packet under the circumstance of the advancement in link technologies and the growth of the number of the Internet users. Many binary search algorithms have been proposed for fast IP address lookup. However, tree-based binary search algorithms are usually unbalanced, and they do not provide very good search performance. Even for binary search algorithms providing balanced search, they have drawbacks requiring prefix duplication. In this paper, a new binary search algorithm which provides the balanced binary search and the number of its entries is much less than the number of original prefixes. This is possible because of composing the binary search tree only with disjoint prefixes of the prefix set. Each node has a prefix vector that has the prefix nesting information. The number of memory accesses of the proposed algorithm becomes much less than that of prior binary search algorithms, and hence its performance for IP address lookup is considerably improved.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.479-482
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• 1998

Whether a given tree is a subgraph of the interconnection network topology is one of the important problem in parallel computing. Trees are used as the underlying structure for divide and conquer algorithms and provide the solution spaces for NP-complete problems. Complete binary trees are the basic structure among those trees. Binomial trees play an important role in broadcasting messages in parallel networks. If binomial trees can be efficiently embedded in complex binary trees, broadcasting algorithms can be effeciently performed on the interconnection networks. In this paper, we present average dilation 2 embedding of binomial trees in complete binary trees.

• Journal of the Korea Computer Industry Society
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• v.2 no.2
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• pp.203-210
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• 2001

To estimate relational models and test the theoretical hypotheses of binary tree search algorithms, we built binary search trees with random permutations of n (number of nodes) distinct numbers, which ranged from three to seven. Probabilities for building binary search trees corresponding to each possible height and balance factor were estimated. Regression models with variables of number of nodes, height, and average number of comparisons were estimated and the theorem of O(1g(n)) was accepted experimentally by a Lack of Test procedure. Analysis of Variance model was applied to compare the average number of comparisons with three groups by height and balance factor of the trees to test theoretical hypotheses of a binary search tree performance statistically.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.2
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• pp.92-99
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• 2014

This paper proposes the method of facial expression recognition based on decision tree structure. In the image of facial expression, ASM(Active Shape Model) and LBP(Local Binary Pattern) make the local features of a facial expressions extracted. The discriminant features gotten from local features make the two facial expressions of all combination classified. Through the sum of true related to classification, the combination of facial expression and local region are decided. The integration of branch classifications generates decision tree. The facial expression recognition based on decision tree shows better recognition performance than the method which doesn't use that.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.21-26
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• 2004

Color image quantization is a process of selecting a set of colors to display an image with some representative colors without noticeable perceived difference. It is very important in many applications to display a true color image in a low cost color monitor or printer. The basic problem is how to display 256 colors or less colors, called color palette, In this paper, we propose improved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on the responsibility of human visual system according to changes of three Primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective quality test and WSNR.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5C
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• pp.382-390
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• 2005

Huffman codes are widely used for image and video data transmission. As the increase of real-time data, a lot of studies on effective decoding algorithms and architectures have been done. In this paper, we proposed a balanced binary search tree for Huffman decoding and compared the performance of the proposed architecture with that of previous works. Based on definitions of the comparison of codewords with different lengths, the proposed architecture constructs a balanced binary tree which does not include empty internal nodes, and hence it is very efficient in the memory requirement. Performance evaluation results using actual image data show that the proposed architecture requires small number of table entries, and the decoding time is 1, 5, and 2.41 memory accesses in minimum, maximum, and average, respectively.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.5C
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• pp.514-522
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• 2003

Contrary to the previous methods, in this paper, we propose an enhanced shot change detection method using multiple features and binary decision tree. The previous methods usually used single feature and fixed threshold between consecutive frames. However, contents such as color, shape, background, and texture change simultaneously at shot change points in a video sequence. Therefore, in this paper, we detect the shot changes effectively using multiple features, which are supplementary each other, rather than using single feature. In order to classify the shot changes, we use binary classification tree. According to this classification result, we extract important features among the multiple features and obtain threshold value for each feature. We also perform the cross-validation and droop-case to verify the performance of our method. From an experimental result, it was revealed that the EI of our method performed average of 2% better than that of the conventional shot change detection methods.

• Journal of IKEEE
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• v.14 no.2
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• pp.24-32
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• 2010

Slotted-ALOHA and Binary-tree method are researched for the anti-collision for RFID system. However, it is required of the rapid recognition time for all tags and the reduction of the system complexity. In this paper. the hybrid anti-collision method is proposed to solve the problems. The RFID reader with the hybrid anti-collision method groups the tags with the number which makes the maximum system throughput, then it reads each group by slotted-ALOHA method. By the computer simulation results, it is found that the hybrid method improves the tag identification time and the system throughput together with the comparison to other anti-collision methods. Therefore, the proposed hybrid anti-collision method will enhance the RFID system performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2342-2348
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• 1999

DCT-based codebook design using binary tree was proposed to reduce computation time and to solve the initial codebook problem. In this method, DCT coefficient of training vectors that has maximum variance is to be a split key and the mean of coefficients at the location is used as split threshold, then balanced binary tree for final codebook is formed. However edge degradation appears in the reconstructed image, since the blocks of shade region are frequently selected for codevector. In this paper, we propose DCT-based vector quantization codebook design using unbalanced binary tree. Above all, the node that has the largest split key is splited. So the number of edge codevector can be increased. From the simulation results, this method reconstructs the edge region sincerely and shows higher PSNR than previous methods.