• Journal of the Institute of Convergence Signal Processing
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• v.7 no.4
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• pp.155-160
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• 2006

This paper presents the hierarchical block matching algorithm using the 4 subbands of the wavelet transformation and the thresholding method. The proposed algorithm improves the PSNR performance of the reconstructed image using the 4 subbands of the wavelet transformation and reduces the computational complexity by thresholding the motion vector. The experimental results of the proposed algorithm for 'Carphone' image and 'Mother and Daughter' image show that if the thresholding value is 0, the computational complexity is increasing up to 16% and the PSNR performance of the reconstructed image improves the 0.16dB in comparison with that of the existing. hierarchical motion estimation algorithm. In addition, as the thresholding value is increasing, the computational complexity reduces up to 8% and the PSNR performance of the reconstructed image is similar.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.99-102
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• 2009

In this paper a hierarchical stereo matching algorithm based on feature extraction is proposed. The boundary (edge) as feature point in an image is first obtained by segmenting an image into red, green, blue and white regions. With the obtained boundary information, disparities are extracted by matching window on the image boundary, and the initial disparity map is generated when assigned the same disparity to neighbor pixels. The final disparity map is created with the initial disparity. The regions with the same initial disparity are classified into the regions with the same color and we search the disparity again in each region with the same color by changing block size and search range. The experiment results are evaluated on the Middlebury data set and it show that the proposed algorithm performed better than a phase based algorithm in the sense that only about 14% of the disparities for the entire image are inaccurate in the final disparity map. Furthermore, it was verified that the boundary of each region with the same disparity was clearly distinguished.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.23-25
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• 2010

In this paper, we studied linking method for updating navigation map with new address map. This method is hierarchical as we chose candidate using attribute data for geometry matching. Limiting a matching range, we conducted a experiment ICP with geometry matching. As a result, for linking method it's quite satisfied but for updating method, we decided that we have to do more precise method for updating.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.1
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• pp.45-52
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• 2015

The interoperability of multi-source data has become more important due to various digital maps, produced from public institutions and enterprises. In this study, the automatic matching algorithm of multi-source building data using hierarchical matching was proposed. At first, we divide digital maps into blocks and perform the primary geometric registration of buildings with the ICP algorithm. Then, corresponding building pairs were determined by evaluating the similarity of overlap area, and the matching threshold value of similarity was automatically derived by the Otsu binary thresholding. After the first matching, we extracted error matching candidates buildings which are similar with threshold value to conduct the secondary ICP matching and to make a matching decision using turning angle function analysis. For the evaluation, the proposed method was applied to representative public digital maps, road name address map and digital topographic map 2.0. As a result, the F measures of matching and non-matching buildings increased by 2% and 17%, respectively. Therefore, the proposed method is efficient for the matching of building polygons from multi-source digital maps.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.88-95
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• 2011

Stereo matching is the research area that regarding the estimation of the distance between objects and camera using different view points and it still needs lot of improvements in aspects of speed and accuracy. This paper presents a fast stereo matching algorithm based on plane-converging belief propagation that uses message passing convergence in hierarchical belief propagation. Also, stereo matching technique is developed using GPU and it is available for real-time applications. The error rate of proposed Plane-converging Belief Propagation algorithm is similar to the conventional Hierarchical Belief Propagation algorithm, while speed-up factor reaches 2.7 times.

• Korean Journal of Remote Sensing
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• v.25 no.3
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• pp.263-270
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• 2009

Noise band removal is a crucial step before spectral matching since the noise bands can distort the typical shape of spectral reflectance, leading to degradation on the matching results. This paper proposes a statistical noise band removal method for hyperspectral data using the correlation coefficient between two bands. The correlation coefficient measures the strength and direction of a linear relationship between two random variables. Considering each band of the hyperspectral data as a random variable, the correlation between two signal bands is high; existence of a noisy band will produce a low correlation due to ill-correlativeness and undirected ness. The unsupervised k-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID in order to evaluate the validation of the proposed method. This paper also proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures. The experimental results conducted on a 228-band hyperspectral data show that while the SAM measure is rather resistant, the performance of SID measure is more sensitive to noise.

• Journal of Korea Multimedia Society
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• v.6 no.7
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• pp.1189-1199
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• 2003

This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using tile pipeline and the data flow technique. The proposed method has been implemented by using an embedded system. The proposed block matching algorithm has been implemented on PLDs(Programmable Logic Device) and clustering algorithm has been implemented by ARM processor. Experimental results show that the proposed system detects the motion of vehicles in real-time.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.779-785
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• 2002

This paper presents a phase-based stereo matching algorithm in order to efficiently extract 3-dimensional objects from two 2D images. Conventional phase-based methods, especially using windowed Fourier phases, inherit good properties in the case of hierarchical approaches, because they basically use a multi-resolution phase map. On the contrary, their computational costs are very heavy. Therefore, a fast hierarchical approach, using multi-resolution phase-based strategy and reducing the redundancy of phase calculations, is proposed in this pare. In addition, a structural matching algorithm on the phase domain is adopted to improve the matching quality. In experimental results, it is shown that the computation loads are considerably reduced about 8 times and stable outputs are obtained.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.1
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• pp.63-71
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• 1988

In this paper, a fast matching method using hierarchical neighborhood search and subtemplate to reduce very heavy computational load of the conventional matching method, is presented. Some parameters of the proposed method are chosen so that an automatic target tracker to which it is applied can track one moving object well in comparatively simple background. Experimental results show that its performance is not so degraded in spite of high computational reduction over that of the matching method using 3-step search.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.51-55
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• 1991

This paper describes an algorithm of pattern analysis of ECG signals by significant points extraction method. The significant points can be extracted by modified zerocrossing method, which method determines the real significant point among the significant point candidates by zerocrossing method and slope rate of left side and right side. This modified zerocrossing method improves the accuracy of detection of real significant point position. This paper also describes the pattern matching algorithm by a hierarchical AND/OR graph of ECG signals. The decomposition of ECG signals by a hierarchical AND/OR graph can make the pattern matching process easy and fast. Furthermore the pattern matching to the significant points reduces the processing time of ECG analysis.