• Journal of the Institute of Electronics Engineers of Korea CI
• /
• v.47 no.1
• /
• pp.92-103
• /
• 2010

In this paper, a method for the recognition of dynamic hand gestures in various backgrounds using Dynamic Space Time Warping(DSTW) algorithm is proposed. The existing method using DSTW algorithm compares multiple candidate hand regions detected from every frame of the query sequence with the model sequences in terms of the time. However the existing method can not exactly recognize the models because a false path can be generated from the candidates including not-hand regions such as background, elbow, and so on. In order to solve this problem, in this paper, we use the invariant moments extracted from the candidate regions of hand and compare the similarity of invariant moments among candidate regions. The similarity is utilized as a weight and the corresponding value is applied to the matching cost between the model sequence and the query sequence. Experimental results have shown that the proposed method can recognize the dynamic hand gestures in the various backgrounds. Moreover, the recognition rate has been improved by 13%, compared with the existing method.

• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.8
• /
• pp.47-54
• /
• 1998

With the increasing popularity of the use of large-volume image database in various application, it becomes imperative to build an efficient and fast retrieval system to browse through the entire database. We present a new method for a content-based image retrieval by using a variable block size and block matching algorithm. Proposed approach is reflecting image features that exploit visual cues such as color and space allocation of image and is getting the fast retrieval time by automatical convergence of retrieval times which adapt to wanting similarity value. We have implemented this technique and tested it for a database of approximately 150 images. The test shows that a 1.9 times fast retrieval time compare to J & V algorithm at the image retrieval efficiency 0.65 and that a 1.83 times fast retrieval time compare to predefined fixed block size.

• Journal of the Korea Convergence Society
• /
• v.12 no.7
• /
• pp.53-60
• /
• 2021

LOD-based recommender systems usually leverage the data available within LOD datasets, such as DBpedia, in order to recommend items(movies, books, music) to the end users. These systems use a semantic similarity algorithm that calculates the degree of matching between pairs of Linked Data resources. In this paper, we proposed a new approach to measuring semantic distance in an LOD-based recommender system by assigning weights converted from user ratings to links in the LOD graph. The semantic distance measurement model proposed in this paper is based on a processing step in which a graph is personalized to a user through weight calculation and a method of applying these weights to LDSD. The Experimental results showed that the proposed method showed higher accuracy compared to other similar methods, and it contributed to the improvement of similarity by expanding the range of semantic distance measurement of the recommender system. As future work, we aim to analyze the impact on the model using different methods of LOD-based similarity measurement.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.2
• /
• pp.99-105
• /
• 2017

Generally, stereo matching methods are used to estimate depth information based on color and spatial similarity. However, most depth estimation methods suffer from the occlusion region because occlusion regions cause inaccurate depth information. Moreover, they do not consider the temporal dimension when estimating the disparity. In this paper, we propose a temporal stereo matching method, considering occlusion and disregarding inaccurate temporal depth information. First, we apply a global stereo matching algorithm to estimate the depth information, we segment the image to occlusion and non-occlusion regions. After occlusion detection, we fill the occluded region with a reasonable disparity value that are obtained from neighboring pixels of the current pixel. Then, we apply a temporal disparity estimation method using the reliable information. Experimental results show that our method detects more accurate occlusion regions, compared to a conventional method. The proposed method increases the temporal consistency of estimated disparity maps and outperforms per-frame methods in noisy images.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.8 no.8
• /
• pp.2913-2929
• /
• 2014

Traditional vector quantization (VQ) schemes encode image blocks as VQ indices, in which there is significant similarity between the image block and the codeword of the VQ index. Thus, the method can compress an image and maintain good image quality. This paper proposes a novel lossless VQ indices compression algorithm to further compress the VQ index table. Our scheme exploits the high correlation of adjacent image blocks to search for the same VQ index with the current encoding index from the neighboring indices. To increase compression efficiency, codewords in the codebook are sorted according to the degree of similarity of adjacent VQ indices to generate a state codebook to find the same index with the current encoding index. Note that the repetition indices both on the search path and in the state codebooks are excluded to increase the possibility for matching the current encoding index. Experimental results illustrated the superiority of our scheme over other compression schemes in the index domain.

• IEIE Transactions on Smart Processing and Computing
• /
• v.4 no.5
• /
• pp.311-317
• /
• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• Journal of the Korea Computer Industry Society
• /
• v.2 no.8
• /
• pp.1117-1122
• /
• 2001

Recently, issues on the internet searching of image information through various multimedia databases have drawn an tremendous attention and several researches on image information retrieval methods are on progress. By incorporating wavelet transform and correlation matrixes, we propose a novel and highly efficient feature vector extraction algorithm that has an capability of a robust similarity matching. The simulation results have yielded a faster and highly accurate candidate image retrieval performance in comparison to those of the conventional algorithms. Such an improved performance can be obtained because the used feature vectors were compressed to 256：1 while the correlation matrixes are incorporated to provide a fuel information for the better matching.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.8
• /
• pp.51-58
• /
• 2009

In this paper. we propose search algorithm using Low Peak Feature of audio and image color value by which similar movies can be identified. Combing through entire video files for the purpose of recognizing and retrieving matching movies requires much time and memory space. Moreover, these methods still share a critical problem of erroneously recognizing as being different matching videos that have been altered only in resolution or converted merely with a different codec. Thus we present here a similar-video-retrieval method that relies on analysis of audio patterns, whose peak features are not greatly affected by changes in the resolution or codec used and image color values. which are used for similarity comparison. The method showed a 97.7% search success rate, given a set of 2,000 video files whose audio-bit-rate had been altered or were purposefully written in a different codec.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 1996.06b
• /
• pp.72-76
• /
• 1996

We propose a novel algorithm for fractal video sequence coding, based on the circular prediction mapping (CPM), in which each range block is approximated by a domain block in the circularly previous frame. In our approach, the size of the domain block is set to be same as that of the range block for exploiting the high temporal correlation between the adjacent frames, while most other fractal coders use the domain block larger than the range block. Therefore the domain-range mapping in the CPM is similar to the block matching algorithm in the motion compensation techniques, and the advantages of this similarity are discussed. Also we show that the CPM can be combined with non-contractive inter-frame mapping (NCIM), improving the performance of the fractal sequence coder further. The computer simulation results on real image sequences demonstrate that the proposed algorithm provides very promising performance at low bit-rate, ranging from 40 Kbps to 250 Kbps.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.37 no.3
• /
• pp.79-87
• /
• 2000

In this paper, we propose a model based moving object tracking algorithm In dynamic scenes To adapt shape change of the moving object, the Hausdorff distance is applied as the measurement of similarity between model and image To reduce processing time, 2D logarithmic search method is applied for locate the position of moving object Experiments on a running vehicle and motorcycle, the result showed that the mean square error of real position and tracking result is 1150 and 1845; matching times are reduced average 1125times and 523 times than existing algorithm for vehicle image and motorcycle image, respectively It showed that the proposed algorithm could track the moving object accurately.