• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.390-395
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• 2009

The robustness of audio fingerprinting system in a noisy environment is a principal challenge in the area of content-based audio retrieval. The selected feature for the audio fingerprints must be robust in a noisy environment and the computational complexity of the searching algorithm must be low enough to be executed in real-time. The audio fingerprint proposed by Philips uses expanded hash table lookup to compensate errors introduced by noise. The expanded hash table lookup increases the searching complexity by a factor of 33 times the degree of expansion defined by the hamming distance. We propose a new method to improve noise robustness of audio fingerprinting in noise environment using predominant pitch which reduces the bit error of created hash values. The sub-fingerprint of our approach method is computed in each time frames of audio. The time frame is transformed into the frequency domain using FFT. The obtained audio spectrum is divided into 33 critical bands. Finally, the 32-bit hash value is computed by difference of each bands of energy. And only store bits near predominant pitch. Predominant pitches are extracted in each time frames of audio. The extraction process consists of harmonic enhancement, harmonic summation and selecting a band among critical bands.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.3
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• pp.249-255
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• 2017

The finger vein recognition technology is a method to acquire a finger vein image by illuminating infrared light to the finger and to authenticate a person through processes such as feature extraction and matching. In order to recognize a finger vein, a 2D mask-based two-dimensional convolution method can be used to detect a finger edge but it takes too much computation time when it is applied to a low cost micro-processor or micro-controller. To solve this problem and improve the recognition rate, this study proposed an extraction method for the region of interest based on virtual core points and moving average filtering based on the threshold and absolute value of difference between pixels without using 2D convolution and 2D masks. To evaluate the performance of the proposed method, 600 finger vein images were used to compare the edge extraction speed and accuracy of ROI extraction between the proposed method and existing methods. The comparison result showed that a processing speed of the proposed method was at least twice faster than those of the existing methods and the accuracy of ROI extraction was 6% higher than those of the existing methods. From the results, the proposed method is expected to have high processing speed and high recognition rate when it is applied to inexpensive microprocessors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.4
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• pp.833-839
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• 2016

In this paper, we propose a selective feature extraction algorithm between Markov transition probability and co-occurrence probability for an effective image splicing detection. The Features used in our method are composed of the difference values between DCT coefficients in the adjacent blocks and the value of Kullback-Leibler divergence(KLD) is calculated to evaluate the differences between the distribution of original image features and spliced image features. KLD value is an efficient measure for selecting Markov feature or Co-occurrence feature because KLD shows non-similarity of the two distributions. After training the extracted feature vectors using the SVM classifier, we determine whether the presence of the image splicing forgery. To verify our algorithm we used grid search and 6-folds cross-validation. Based on the experimental results it shows that the proposed method has good detection performance with a limited number of features compared to conventional methods.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.55-67
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• 1998

This paper presents an automatic facial feature point extraction algorithm in sequential color images. To extract facial region in the video sequence, a moving color detection technique is proposed that emphasize moving skin color region by applying motion detection algorithm on the skin-color transformed images. The threshold value for the pixel difference detection is also decided according to the transformed pixel value that represents the probability of the desired color information. Eye candidate regions are selected using both of the black/white color information inside the skin-color region and the valley information of the moving skin region detected using morphological operators. Eye region is finally decided by the geometrical relationship of the eyes and color histogram. To decide the exact feature points, the PCA(Principal Component Analysis) is used on each eye and mouth regions. Experimental results show that the feature points of eye and mouth can be obtained correctly irrespective of background, direction and size of face.

• Journal of Korea Multimedia Society
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• v.13 no.3
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• pp.410-416
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• 2010

This paper presents the auto-extraction method that searches for the Mapping points in the calibration algorithm of the image acquired by the wide angle CCD camera. In this algorithm, we remove the noise from the distorted image and then obtain the edge image. Proposed method extracts the distortion point, comparing the threshold value of the histogram of the horizontal and vertical pixel lines in edge image. This processing step can be directly applied to the original image of the wide angle CCD camera output. Proposed method results are compared with hand-worked result image using the two wide angle CCD cameras having different angles with the difference value of the result images respectively. Experimental results show that proposed method can allocate the distortion-calibration constant of the wide angle CCD camera regardless of lens type, distortion shape and image type.

• Korean Journal of Remote Sensing
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• v.32 no.5
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• pp.471-482
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• 2016

This paper presents an extraction method for water body which uses block-based image partitioning and extension of water body boundaries to improve the performance of supervised classification for water body extraction. The Mahalanobis distance image is created by computing the spectral information of Normalized Difference Water Index (NDWI) and Near Infrared (NIR) band images over a training site within the water body in order to extract an initial water body area. To reduce the effect of noise contained in the Mahalanobis distance image, we apply mean curvature diffusion to the image, which controls diffusion coefficients based on connectivity strength between adjacent pixels and then extract the initial water body area. After partitioning the extracted water body image into the non-overlapping blocks of same size, we update the water body area using the information of water body belonging to water body boundaries. The update is performed repeatedly under the condition that the statistical distance between water body area belonging to water body boundaries and the training site is not greater than a threshold value. The accuracy assessment of the proposed algorithm was tested using KOMPSAT-2 images for the various block sizes between $11{\times}11$ and $19{\times}19$. The overall accuracy and Kappa coefficient of the algorithm varied from 99.47% to 99.53% and from 95.07% to 95.80%, respectively.

• Journal of Korea Multimedia Society
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• v.13 no.7
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• pp.1062-1075
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• 2010

In the medical image application the difference of intensity is widely used for the image segmentation and feature extraction, and a well known method is the threshold technique that determines a threshold value and generates a binary image based on the threshold. A frequently-used threshold technique is the Otsu algorithm that provides efficient processing and effective selection criterion for choosing the threshold value. However, we cannot get good segmentation results by applying the Otsu algorithm to chest X-ray images. It is because there are various organic structures around lung regions such as ribs and blood vessels, causing unclear distribution of intensity levels. To overcome the ambiguity, we propose in this paper an effective algorithm to extract pulmonary regions that utilizes the Otsu algorithm after removing the background of an X-ray image, constructs intensity-level maps, and uses them for segmenting the X-ray image. To verify the effectiveness of our method, we compared it with the existing 1-dimensional and 2-dimensional Otsu algorithms, and also the results by expert's naked eyes. The experimental result showed that our method achieved the more accurate extraction of pulmonary regions compared to the Otsu methods and showed the similar result as the naked eye's one.

• Korean Journal of Plant Resources
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• v.16 no.3
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• pp.187-193
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• 2003

To determine the properties for juice preperation of Black Omija (Schizandra nigra Max.) and Omija (Schizandra chinensis), yield of extraction, chromaticity and lightness, pH and soluble solid of the extract were investigated. The rate of extract yield from Schizandra nigra was highest when extracted for 3 hours at 80$^{\circ}C$ in 20％ ethanol solution. For the desirable chromaticity coordinates, the optimum extraction time and temperature of Schizandra nigra extract were 3 hours at 80$^{\circ}C$. The lightness of the extract was low of the value when extraction time and temperature was long and high. The sugar content of the extract of S. nigra was 2.0­2.6％ Brix, lower than that of S. chinensis, but the difference was insignificant. The pH of the extract from S. nigra was 0.1­0.2 higher than that of S. chinensis. Although the pH of the extract from S. nigra was a little low when extracted by water, the pH range was enough to maintain the stability of color of extract from the S. chinensis.

• Magazine of the Korean Society of Agricultural Engineers
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• v.29 no.2
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• pp.23-29
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• 1987

This study was fulfilled by the floating lysimeter method at the experimental farm of Kon-Kuk University from August to November of 1986 to investigate the amount of evapotranspiration by the growing periods, evapotranspiration ratio, amount of watering per one time, days of intermission, soil moisture extraction pattern and crop coefficient of the Chinese cabbage cultivated in the sandy loam soil at the watering point of pF2.O. The results obtained are summarized as follows: 1.The total evapotranspiration during the growing period was 267.2mm, which was 3. 99mm by daily average, and the maximum evapotranspiration showed in the mid ten days of September with the value of 5.81mm I day. 2.The evapotranspiration ratio by the growing stages increased from the last ten days of September and showed maximum in the beginning of October, and the average evapotranspiration ratio was 1.4. 3.The days of watering intermission at the watering point of pF2.O was 2.4 days, and the average yield per plant was 3,228 g. 4. The soil moisture extraction pattern in the initial stage was 78.9 % in the 1st and 2nd soil layer and 21.1 % in the 3rd and 4th layer, and the mid-season stage, the moisture extraction proportion of the under layer accounted for 38.8 % which showed that the root elongated to the lowest soil layer. 5.The average crop coefficient(Kc) of the tested crop during the growing period was 0.67 by Penman equation and 2.36 by Pan Evaporation equation, which showed high difference by the calculation methods, and the changes of crop coefficient by the growing stages by Penman equation was favorable than those calculated by other met-hods.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2010.03a
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• pp.16-16
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• 2010

GaN-based light-emitting diodes (LEDs) are attracting great interest as candidates for next-generation solid-state lighting, because of their long lifetime, small size, high efficacy, and low energy consumption. However, for general illumination applications, the external quantum efficiency of LEDs, determined by the internal quantum efficiency (IQE) and the light extraction efficiency, must be further increased. The IQE is determined by crystal quality and epitaxial layer structure and high value of IQE more than 70% for blue LEDs have been already reported. However, there is much room for improvement of light extraction efficiency because most of the generated photons from active layer remain inside LEDs by total internal reflection at the interface of semiconductor with air due to the high refractive index difference between LEDs epilayer (for GaN, n=2.5) and air (n=1). The light confining in LEDs will be reabsorbed by the metal electrode or active layer, reducing the efficacy of LEDs. Here, we present the first demonstration of enhanced light extraction by forming a MgO nano-pyramids structure on the surface of vertical-LEDs. The MgO nano-pyramids structure was successfully fabricated at room temperature using conventional electron-beam evaporation without any additional process. The nano-sized pyramids of MgO are formed on the surface during growth due to anisotropic characteristics between (111) and (200) plane of MgO. The ZnO layer with quarter-wavelength in thickness is inserted between GaN and MgO layers to increase the critical angle for total internal reflection, because the refractive index of ZnO (n=1.94) could be matched between GaN (n=2.5) and MgO (n=1.73). The MgO nano-pyramids structure and ZnO refractive-index modulation layer enhanced the light extraction efficiency ofV-LEDs with by 49%, comparing with the V-LEDs with a flat n-GaN surface. The angular-dependent emission intensity shows the enhanced light extraction through the side walls of V-LEDs as well as through the top surface of the n-GaN, because of the increase in critical angle for total internal reflection as well as light scattering at the MgO nano-pyramids surface.