• The KIPS Transactions:PartB
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• v.12B no.6 s.102
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• pp.715-720
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• 2005

This paper presents a hybrid recognition method of first moment of face image and principal component analysis(PCA). First moment is applied to reduce the dimension by shifting to the centroid of image, which is to exclude the needless backgrounds in the face recognitions. PCA is implemented by single layer neural network which has a teaming rule of Foldiak algorithm. It has been used as an alternative method for numerical PCA. PCA is to derive an orthonormal basis which directly leads to dimensionality reduction and possibly to feature extraction of face image. The proposed method has been applied to the problems for recognizing the 48 face images(12 Persons $\ast$ 4 scenes) of 64$\ast$64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate). The negative angle has been relatively achieved more an accurate similarity than city-block or Euclidean.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.174-181
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• 2011

A new registration method for IR image and EO image is proposed in this paper. IR sensor is applicable to many area because it absorbs thermal radiation energy unlike EO sensor does. However, IR sensor has difficulty to extract and match features due to low contrast compared to EO image. In order to register both images, we used modified SIFT(Scale Invariant Feature Transform) and block processing to increase feature distinctiveness. To remove outlier, we applied RANSAC(RANdom SAample Concensus) for each block. Finally, we unified matching features into single coordinate system and remove outlier again. We used 3~5um range IR image, and our experiment result showed good robustness in registration with IR image.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.7-14
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• 2006

This paper presents an efficient face recognition method using both first moment of image and basis images. First moment which is a method for finding centroid of image, is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. Basis images which are the face features, are respectively extracted by principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). This is to improve the recognition performance by excluding the redundancy considering to second- and higher-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 48 face images(12 persons*4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed methods has a superior recognition performances(speed, rate) than conventional PCA and FP-ICA without preprocessing, the proposed FP-ICA has also better performance than the proposed PCA. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.33-40
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• 2006

This paper presents an efficient face recognition method using both first moment of image and eigenvector. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shitting to the centroid of face image. Eigenvector which are the basis images as face features, is extracted by principal component analysis(PCA). This is to improve the recognition performance by excluding the redundancy considering to second-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 60 face images(15 persons *4 scenes) of 320*243 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. In case of the 45 face images, the experimental results show that the recognition rate of the proposed methods is about 1.6 times and its the classification is about 5.6 times higher than conventional PCA without preprocessing. The city-block has been relatively achieved more an accurate classification than Euclidean or negative angle.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.5
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• pp.581-587
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• 2005

This paper presents a hybrid face recognition method of both the first moment of image and the independent component analysis(ICA) of fixed point(FP) algorithm based on Newton method. First moment is a method for finding centroid of image, which is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. FP-ICA is also applied to find a set of independent basis images for the faces, which is a set of statistically independent facial features. The proposed method has been applied to the problem for recognizing the 48 face images(12 persons o 4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed method has a superior recognition performances(speed, rate) than conventional FP-ICA without preprocessing. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.1-6
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• 2019

One method for image recognition is template matching. In conventional template matching, the block matching algorithm (BMA) is performed while changing the two-dimensional translational displacement of the template within a given matching image. The template size and shape do not change during the BMA. Since only two-dimensional translational displacement is considered, the success rate decreases if the size and direction of the object do not match in the template and the matching image. In this paper, a variable is added to adjust the two-dimensional direction and size of the template, and the optimal value of the variable is automatically calculated in the block corresponding to each two-dimensional translational displacement. Using the calculated optimal value, the template is automatically transformed into an optimal template for each block. The matching error value of each block is then calculated based on the automatically deformed template. Therefore, a more stable result can be obtained for the difference in direction and size. For ease of use, this study focuses on designing the algorithm in a closed form that does not require additional information beyond the template image, such as distance information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.2
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• pp.203-211
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• 2009

With supply of the domestic digital camera, the relative importance of the digital camera is coming to be high gradually on aerial photogrammetry, the image of digital camera is more applied in image map or digital topographic map production. But, there are cases that do not have position information or attitude information of each photograph in digital camera results. Therefore, we wish to present additional method to get more accurate photograph control point result. In this study, One is called A method, which is the case of entering positioning information of principal point from topographic map as default values that are need to extract tie point automatically using by 56 pieces of photography that are photographed by DMC to the extent to 5 courses and 35 GCP points. The other is called B-method, which is the case of entering exterior orientation parameters that are processed by block adjustment for A-method using by 4 control points in method-1 as default values. We have analyzed about results per control points arrangement for two cases using MATCH-AT that is photograph control point measurement S/W of Germany INPHO company. As a result of analysis, accuracy of B-method was better than that of A-method, and we could get more accurate results if block adjustments are executed including self calibration. Also, it is more effective in expense side that using self calibration for photograph survey in B-method because can reduce GCP numbers.

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.441-447
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• 2000

Automatic word spacing is needed to solve the automatic indexing problem of the non-spaced documents and the space-insertion problem of the character recognition system at the end of a line. We propose a word spacing algorithm that automatically finds out word spacing positions. It is based on the recognition of Eojeol components by using the sentence partition and bidirectional longest-match algorithm. The sentence partition utilizes an extraction of Eojeol-block where the Eojeol boundary is relatively clear, and a Korean morphological analyzer is applied bidirectionally to the recognition of Eojeol components. We tested the algorithm on two sentence groups of about 4,500 Eojeols. The space-level recall ratio was 97.3% and the Eojeol-level recall ratio was 93.2%.

• Journal of IKEEE
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• v.2 no.2 s.3
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• pp.285-293
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• 1998

This paper presents unequal error protection and error concealment techniques far robust H.263 video transmission over mobile channels. The proposed error protection scheme has three major features. First, it has the capability of preventing the loss of synchronization information in H.263 video stream as much as possible that the H.263 decoder can resynchronize at the next decoding point, if errors are occurred. Secondly, it employs an unequal error protection scheme to support variable coding rates using rate compatible punctured convolutional (RCPC) codes, dividing the encoded stream into two classes. Finally, a macroblock-interleaving scheme is employed in order to minimize the corruption of consecutive macroblocks due to burst errors, which can make a proper condition for error concealment. In addition, to minimize the spatial error propagations due to the variable length codes, a fast resynchronization scheme at the group of block layer is developed for recovering subsequent error-free macroblocks following the damaged macroblock. futhermore, error concealment techniques based on both side match criterion and overlapped block motion compensation (OBMC) are employed at the source decoder so that it can not only recover the lost macroblock more accurately, but also reduce blocking artifacts. Experimental results show that the proposed scheme can be an effective error protection scheme since proper video quality can be maintained under various channel bit error rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.257-263
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• 2003

Error control and concealment in video communication is becoming increasingly important because transmission errors can cause single or multiple loss of macroblocks in video delivery over unreliable channels such as wireless networks and the internet. This paper describes a temporal error concealment by postprocessing. Lost image blocks are overlapped block motion compensated (OBMC) using median of motion vectors from adjacent blocks at the decoder. The results show a significant improvement over zero motion error concealment and other temporal concealment methods such as Motion Vector Rational Interpolation or Side Match Criterion OBMC by 1.4 to 3.5㏈ gain in PSNR. We present experimental results showing improvements in PSNR and computational complexity.