• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.40-47
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• 1997

This paper proposes a method using the straight line Hough transform(SLHT) that recognizes the position of DNA band images from the scanner. The method also detects and corrects automatically the leaning angle of the image. After binarization of a gray-scale DNA band images, the SLHT detects line components involved in the image and recognizes the position of the image using the cross paints of the line components assuming the image is in retangular shape. To improve efficiency of reading many IINA band images through the scanner, this method finds and corrects the leaning angle accurately as less than -t I degree.

• KIEE International Transactions on Electrophysics and Applications
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• v.4C no.6
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• pp.272-275
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• 2004

A balanced single side-band (SSB) mixer employing a sub-harmonic configuration is designed for up and down conversions in K-band. The designed mixer uses anti-parallel diode (APD) pairs to effectively eliminate even harmonics of the local oscillator (LO) spurious signal. To reduce the odd harmonics of LO at the RF port, we employ a balanced configuration for LO. The fabricated chip shows 12$\pm$2dB of conversion loss and image-rejection ratio of about 20dB for down conversion at RF frequencies of 24-27.5GHz. As an up-conversion mode, the designed chip shows 12dB of conversion loss and image-rejection ratio of 20 ～ 25 dB at RF frequencies of 25 to 27GHz. The odd harmonics of the LO are measured below -37dBc.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.5
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• pp.1041-1046
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• 2009

In this paper, we proposed a robust watermark scheme for image based on SVD(Singular Value Transform) and Triplet. First, the original image is decomposed by using 3-level DWT, and then used the singular values changed for embedding and extracting of the watermark sequence in LL3 band. Since the matrix of singular values is not easily altered with various signal processing noises, the embedded watermark sequence has the ability to withstand various signal processing noise attacks. Nevertheless, this method does not guarantee geometric transformation(such as rotation, cropping, etc.) because the geometric transformation changes the matrix size. In this case, the watermark sequence cannot be extracted. To compensate for the above weaknesses, a method which uses the triplet for embedding a barcode image watermark in the middle of frequency band is proposed. In order to generate the barcode image watermark, the pattern of the watermark sequence embedded in a LL3 band is used. According to this method, the watermark information can be extracted from attacked images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.8
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• pp.1722-1732
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• 1997

In this paper, we propose a coding method of remotely sensed satellite image data using region classification and interband correlation. This method classifies each pixel vector consider spectral characteristics. Then we perform the classified intraband VQ to remove spatial (intraband redundancy for a reference band image. To remove interband redundancy effectively, we perform the classified interband prediction for the band images that the high correlation spectrally and perform the classified interband VQ for the remaining band images. Experiments on LANDSAT TM image show that the coding efficiency of the proposed method is better than that of the conventional Gupta's method. Especially, this method removes redundancies effectively for satellite iamge including various geographical objects and for and images that have low interband correlation.

• Journal of Fashion Business
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• v.10 no.4
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• pp.70-77
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• 2006

The purpose of this study is to evaluate the differences of visual image by variations in the location and width of the waist band of the one-piece dress. The stimuli are 24 samples: 8 variations of the location of the waist band and 3 variations of the width of the waist band. The data has been obtained from 50 fashion design majors. The data has analyzed by Factor Analysis, Anova, Scheff's Test and the MCA method. The results of the study are as follows. According to the result of factor analysis of the visual image based on the changes in the location and width of waist bands, three factors were identified- attractiveness, elegance and practicality. Among them, attractiveness was found to be the most important. The visual image was evaluated positively when waist bands were positioned above the natural waist line and negatively when waist bands were positioned below the natural waist line regardless of their width. In addition, the visual image based on the width of waist bands for one-piece dress was the most positive when the width was 4.5cm. No significant difference was observed in the visual image according to band width when the waist bands were positioned below the natural waist line. The interaction of visual image according to the location and width of waist bands for one-piece dress did not appear. As the main effect, significant differences were observed in all of the three factors according to the location of waist bands, but only two factors excluding elegance showed some difference according to the width of waist bands. When multiple classification analysis was applied to the factors without interaction, the location of waist bands appeared to have more significant effect on visual image than the width of waist bands.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.1
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• pp.8-18
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• 2008

In this paper, we propose an efficient algorithm using wavelet transform for still image database retrieval. Especially, it uses only the lowest frequency sub-band in multi-level wavelet transform so that a retrieval system uses a smaller quantity of memory and takes a faster processing time. We extract different textured features, statistical information such as mean, variance and histogram, from low frequency sub-band. Then we measure the distances between the query image and the images in a database in terms of these features. To obtain good retrieval performance, we use the first feature (mean and variance of wavelet coefficients) to filter out most of the unlikely images. The rest of the images are considered to be candidate images. Then we apply the second feature (histogram of wavelet coefficient) to rank all the candidate images. To evaluate the algorithm, we create various distorted image databases using MIT VisTex texture images and PICS natural images. Through simulations, we demonstrate that our method can achieve performance satisfactorily in terms of the retrieval accuracy as well as the both memory requirement and computational complexity. Therefore it is expected to provide good retrieval solution for JPEG-2000 using wavelet transform.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1245-1254
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• 2023

Significant research has been conducted on the W-band synthetic aperture radar (SAR) system that utilizes the 77 GHz frequency modulation continuous wave (FMCW) radar. To reconstruct the high-resolution W-band SAR image, it is necessary to transform the point cloud acquired from the stereo cameras or the LiDAR in the direction of 6 degrees of freedom (DOF) and apply them to the SAR signal processing. However, there are difficulties in matching images due to the different geometric structures of images acquired from different sensors. In this study, we present the method to extract an optimized depth map by obtaining 6 DOF of the point cloud using a gradient descent method based on the entropy of the SAR image. An experiment was conducted to reconstruct a tree, which is a major road environment object, using the constructed W-band SAR system. The SAR image, reconstructed using the entropy-based gradient descent method, showed a decrease of 53.2828 in mean square error and an increase of 0.5529 in the structural similarity index, compared to SAR images reconstructed from radar coordinates.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.314-319
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• 1998

In this paper, for efficient data classification in multispectral bands environment, a band feature extraction method using the Rough sets theroy is proposed. First, we make a look up table from training data, and analyze the properties of experimental multispectral image data, then select the efficient band usin indiscernibility relation of Rough sets theory from analysis results. Proposed method is applied to LAMDSAT TM data on 2, June, 1992. Among them, normal distributive data were experimented, mainly. From this, we show clustering trends that similar to traditional band selection results by wavelength properties, from this, we verify that can use the proposed method that centered on data properties to select the efficient bands, though data sensing environment change to hyperspectral band environments.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.208-211
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• 2008

Band-limited filtering will be applied to remove interference resulted from two neighbored channels in the transmission of KOMPSAT-5 X-Band image data. In that case, receiver in ground station should prepare righteous matched filter to avoid huge BER degradation depending on the matched filter of COTS receiver. As an effort to simulate the bandlimited filtering, test filter was designed and manufactured on the basis of main specification for output filter of KOMPSAT-5 satellite. Consequently, 1.8dB of BER degradation was measured at the output of test band-pass filter, but the degradation was downsized up to 0.4dB thanks to the adaptive matched filter of COTS receiver.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.111-114
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• 2008

The existence of noise bands may deform the typical shape of the spectrum, making the accuracy of clustering degraded. This paper proposes a statistical approach to remove noise bands in hyperspectral data using the correlation coefficient of bands as an indicator. Considering each band as a random variable, two adjacent signal bands in hyperspectral data are highly correlative. On the contrary, existence of a noise band will produce a low correlation. For clustering, the unsupervised ${\kappa}$-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID. Furthermore, this paper 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.