• Food Engineering Progress
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• v.15 no.4
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• pp.324-331
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• 2011

Hyperspectral reflectance imaging technology was used to predict internal quality of cherry tomatoes with the spectral range of 400-1000 nm. Partial least square (PLS) regression method was used to predict firmness, sugar content, and acid content. The PLS models were developed with several preprocessing methods, such as normalization, standard normal variate (SNV), multiplicative scatter correction (MSC), and derivative of Savitzky Golay. The performance of the prediction models were investigated to find the best combination of the preprocessing and PLS models. The coefficients of determination ($R^{2}_{p}$) and standard errors of prediction (SEP) for the prediction of firmness, sugar content, and acid content of cherry tomatoes from green to red ripening stages were 0.876 and 1.875kgf with mean of normalization, 0.823 and $0.388^{\circ}Bx$ with maximum of normalization, and 0.620 and 0.208% with maximum of normalization, respectively.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.577-579
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• 1998

본 논문에서는 디지털 영상 데이터에 워터마크를 삽입하는 알고리즘을 제시한다. 디지털 데이터를 주파수 공간으로 변환시켜 인간이 잘 감지 못하는 주파수 영역과 중요한 주파수를 선택하여 대역확산통신(Spread Spectrum Communication)에서 사용되는 유사한 방법으로 워터마크를 삽입하였다. Fourier 스펙트럼 공간에서 JPEG 압축의 다양한 양자화 단계를 거쳐도 변화가 덜 민감한 Phase에서 워터마크를 삽입할 주파수 영역을 찾았다. 원본과 워터마크가 삽입된 데이터를 가지고 워터마크는 자기상관관계 특성으로 추출하였다. 그리고 다양한 신호처리(손실 압축, 필터링, 양자화)에도 워터마크를 추출하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.45-52
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• 2016

This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.

• Journal of the Mineralogical Society of Korea
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• v.32 no.1
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• pp.63-69
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• 2019

The oxidation states of structural Fe in minerals reflect the paleo-depositional redox conditions for the biologically or abiotically induced mineral formation. Particularly, nano-scale analysis using high-resolution transmission electron microscopy (HRTEM) and electron energy loss spectroscopy (EELS) is necessary to identify evidence for the microbial role in the biomineralization. HRTEM-EELS analysis of oxidation states of structural Fe and carbon bonding structure differentiate biological factors in mineralization by mapping the distribution of Fe(II)/Fe(III) and source of organic C. HRTEM-EELS technique provides geomicrobiologists with the direct nano-scale evidence of microbe-mineral interaction.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.3
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• pp.98-109
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• 2000

While the bispectrum has desirable properties in itself and therefore has a lot of potential to be applied to signal and Image restoration. few real-world application results have appeared in literature The major problem with this IS the difficulty In realizing the expectation operator of the true bispectrum, due to the lack of realizations. In this paper, the true bispectrum is defined as the expectation of the sample bispectrum, which IS the Fourier representation of the triple correlation given one realization The characteristics of the sample bispectrum are analyzed and a way to obtain an estimate of the true bispectrum without stochastic expectation, using the generalized theory of weighted regularization is shown. The bispectrum estimated by the proposed algorithm is experimentally demonstrated to be useful for signal recovery under blurred noisy condition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.861-868
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• 2017

Near band infrared imaging technique has adopted for imaging EL2 and shallow level distributions in undoped semi-insulating LEC GaAs. This technique, which relies on the mapping of near bandgap infrared transmission, is both rapid and non-destructive. Until now no quantitative analysis has been reported for near band edge region which gives the reverse contrast on EL2 absorption images. This paper presents the spectral, spatial and temperature dependence of photoquenching forward and inverse mechanism in the band edge domain for cells and walls and for direct and inverted contrast conditions during transitory regimes. The difference in the threshold for the EL2w and EL2b defects could be attributed to the contribution of a different electrical assistance due to a different species of impurities. Quantitative analysis results show an increased density of EL2w and a small reduction of EL2b in the region of the walls where there is a high density of dislocations.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.10 no.4
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• pp.13-19
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• 2000

With the rapid development of the information communication technology, more and more distribution multimedia data and electronic publishing in the web, has created a need for the copyright protection with authentication of digital information. In this paper, we propose a multi-watermarking adding and adaptive spectral watermark algorithm well adaptive frequency domain of each hierarchical using orthogonal forward wavelet transform(FWT. Numerical test results, created watermarking image robustness not only image transform such as low-pass filtering, bluring, sharpen filtering, wavelet compression but also brightness, contrast gamma correction, histogram equalization, cropping.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.824-833
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• 2004

Due to the bandwidth and storage limitations, medical images are needed to be compressed before transmission and storage. DICOM (Digital Imaging and Communications in Medicine) specification, which is the medical images standard, provides a mechanism for supporting the use of JPEG still image compression standard. In this paper, we explain a method for compressing medical images by JPEG standard and propose two methods for JPEG compression. First, because medical images differ from natural images in optical feature, we propose a method to design adaptively the quantization table using spectrum analysis. Second, because medical images have higher pixel depth than natural images do, we propose a method to design Huffman table which considers the probability distribution feature of symbols. Therefore, we propose methods to design a quantization table and Huffman table suitable for medical images. Simulation results show the improved performance compared to the quantization table and the adjusted Huffman table of JPEG standard. Proposed methods which are satisfied JPEG Standard, can be applied to PACS (Picture Archiving and Communications System).

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.859-872
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• 2016

Land cover classification is an important tool for preventing natural disasters, collecting environmental information, and monitoring natural resources. Hyperspectral imaging is widely used for this task thanks to sufficient spectral information. However, the curse of dimensionality, spatiotemporal variability, and lack of labeled data make it difficult to classify the land cover correctly. We propose a novel classification framework for land cover classification of hyperspectral data based on convolutional neural networks. The proposed framework naturally incorporates full spectral features with the information from neighboring pixels and has advantages over existing methods that require additional feature extraction or pre-processing steps. Empirical evaluation results show that the proposed framework provides good generalization power with classification accuracies better than (or comparable to) the most advanced existing classifiers.

• Korean Journal of Biological Psychiatry
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• v.3 no.2
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• pp.216-221
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• 1996

The quantitative EEGs of obsessive-compulsive disorder patients were analyzed using spectral analysis and compared to age and sex-matched controls. The subjects were 19 patients(men=15, women=4) suffering from obsessive-compulsive disorder(DSM-III-R). Absolute power, relative power and interhemispheric asymmetry of EEG were used to compare obsessive-compulsive disorder patients with controls. In order to fit the EEG data to a normal distribution, a log transformation of power values of every bandwidth in each deviation was calculated prior statistical analysis. The Wilcoxon rank test was performed to compare obsessive-compulsive group to the control group. In obsessive-compulsive disorder, abnormalities of quantitative EEGs are prominent in fronto-central. These results ore compatible with other brain imaging studies of obsessive-compulsive disorder and suggested that fronto-central area plays an important role in the pathophysiology of obsessive-compulsive disorder.