• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.10
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• pp.80-86
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• 2014

A low-noise readout circuit is studied for 2-D capacitive microbolometer focal plane arrays (FPAs). In spite of the merits of the integration method, a simple and effective pixelwise readout circuit without integration is used for input circuit because of a small pixel size and narrow noise bandwidth. To reduce the power consumption and the kT/C noise, which is the dominant noise of the capacitive microbolometer FPAs with small capacitance, a new correlated double sampling (CDS) is used for columnwise circuit. The proposed circuit has been designed using a $0.35-{\mu}m$ 2-poly 4-metal CMOS process for a microbolometer array with a pixel size of $50{\mu}m{\times}50{\mu}m$. The proposed circuit effectively reduces the kT/C noise and the other low-frequency noise of microbolometer, and the noise characteristics of the fabricated chip have been verified by measurements. The rms noise voltage of the proposed circuit is reduced from 30 % to 55 % compared to that of the simple readout input circuit, and the noise equivalent temperature difference (NETD) of the proposed circuit is very low value of 21.5 mK.

• Journal of Korea Water Resources Association
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• v.56 no.6
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• pp.403-417
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• 2023

In this research, a methodology was developed for constructing an appropriate rainfall image database for estimating rainfall intensity based on CCTV video. The database was constructed in the Large-Scale Climate Environment Chamber of the Korea Conformity Laboratories, which can control variables with high irregularity and variability in real environments. 1,728 scenarios were designed under five different experimental conditions. 36 scenarios and a total of 97,200 frames were selected. Rain streaks were extracted using the k-nearest neighbor algorithm by calculating the difference between each image and the background. To prevent overfitting, data with pixel values greater than set threshold, compared to the average pixel value for each image, were selected. The area with maximum pixel variability was determined by shifting with every 10 pixels and set as a representative area (180×180) for the original image. After re-transforming to 120×120 size as an input data for convolutional neural networks model, image augmentation was progressed under unified shooting conditions. 92% of the data showed within the 10% absolute range of PBIAS. It is clear that the final results in this study have the potential to enhance the accuracy and efficacy of existing real-world CCTV systems with transfer learning.

• The Journal of the Korea Contents Association
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• v.12 no.8
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• pp.20-28
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• 2012

DVC(Distributed Video Coding) technique is a new paradigm, which is based on the Slepian-Wolf and Wyner-Ziv theorems. DVC offers not only flexible partitioning of the complexity between the encoder and decoder, but also robustness to channel errors due to intrinsic joint source-channel coding. Many conventional research works have been focused on the light video encoder and its rate-distortion performance improvement. However, in this paper, we propose a new DVC codec which is effectively applicable for error-prone environment. The proposed method adopts a quantiser without dead-zone and symmetric Gray code around zero value. Through computer simulations, the proposed method is evaluated by the bit errors position as well as the number of burst bit errors. Additionally, it is shown that the maximum and minimum transmission rate for the given application can be linearly determined by the number of bit errors.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.814-818
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• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.5
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• pp.518-528
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• 2001

In this paper, we firstly define a new combined segmentation measure and propose a segmentation algorithm using this measure. The combined segmentation measure is a weighted sum of intensity, motion, and a change segmentation measure that is extracted from the resulting image of the proposed change detector. The change segmentation measure is defined as an absolute change value difference between an pixel and its neighboring region from the eroded image, which results from morphological erosion filtering to eliminate many inaccurate components included in the resulting image of a conventional change detector. The change segmentation measure can be used as an efficient segmentation measure for the accurate segmentation of neighboring moving objects and static background regions. Therefore, the proposed combined segmentation measure can determine exact boundaries in the segmentation process of region-based coding even though the estimated motion vectors around the boundaries of moving objects and static background regions are inaccurate and the intensities around the boundaries are similar.

• Korean Journal of Remote Sensing
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• v.27 no.2
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• pp.89-98
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• 2011

Four kinds of gain and offset correction coefficients that are used to correct the nonuniformity between pixels are discussed. And their correction performance has been compared by performing image correction. using the correction coefficients calculated, on the real image data obtained from a newly fabricated camera electronics system. The performance of the correction coefficients depends in general on the number of the light input levels used to obtain the reference image. The result shows that, as expected obviously, when only two light input levles are used to obtain the reference image, even though its correction coefficients are relatively easily calculated, the correction performance is relatively poor. And with the number of light inputs increased to a value of larger than two, the correction performance is improved. It is noted, however, no Significant performance difference is found between the different correction coefficients employed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.767-773
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• 2017

In this paper, we propose a design of Intra prediction angular mode decision for HEVC encoder. Intra prediction coding of HEVC is a method for predicting a current block by referring to samples reconstructed around a current block. Intra prediction supports a total of 35 modes with 1 DC mode, 1 Planar mode, and 33 Angular modes. Intra prediction coding of HEVC works by performing all 35 modes for efficient encoding. However, in order to process all of the 35 modes, the computational complexity and operational time required are high. Therefore, this paper proposes comparing the difference in the value of the original pixel, using an algorithm that determines angular mode efficiently. This new algorithm reduces the Hardware size. The hardware which is proposed was designed using Verilog HDL and was implemented in 65nm technology. Its gate count is 14.9K and operating speed is 2GHz.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.4
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• pp.205-211
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• 2019

Steganalysis is a technique that aims to detect and recover data hidden by steganography. Steganalytic methods detect hidden data by analyzing visual and statistical distortions caused during data embedding. However, for recovering the hidden data, they need to know which steganographic methods the hidden data has been embedded by. Therefore, we propose a hierarchical convolutional neural network (CNN) structure that identifies a steganographic method applied to an input image through multi-level classification. We trained four base CNNs (each is a binary classifier that determines whether or not a steganographic method has been applied to an input image or which of two different steganographic methods has been applied to an input image) and connected them hierarchically. Experimental results demonstrate that the proposed hierarchical CNN structure can identify four different steganographic methods (LSB, PVD, WOW, and UNIWARD) with an accuracy of 79%.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.691-702
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• 2004

In this paper, we propose a sequence of method which extrats ROIs(Region of Interests) rapidly from the parcel image of large size. In the proposed method, original image is spilt into the small masks, and the meaningful masks, the ROIs, are extracted by two criterions sequentially The first criterion is difference of pixel value between Inner points, and the second is deviation of it. After processing, some informational ROIs-the areas of bar code, characters, label and the outline of object-are acquired. Using diagonal axis of each ROI and the feature of various 2D bar code, the area of 2D bar code can be extracted from the ROIs. From an experiment using above methods, various ROIs are extracted less than 200msec from large-size parcel image, and 2D bar code region is selected by the accuracy of 100％.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1301-1314
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• 2022

Normalized Difference Vegetation Index (NDVI) is utilized as an indicator to represent the vegetation condition on the land surface in various applications such as land cover, crop yield, agricultural drought, soil moisture, and forest disaster. However, satellite optical sensors for visible and infrared rays cannot see through the clouds, so the NDVI of the cloud pixel is not a valid value for the land surface. This study proposed a real-time correction of the underestimation noise for GEO-KOMPSAT-2A (GK2A) daily NDVI and made sure its feasibility through the quantitative comparisons with Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and the qualitative interpretation of time-series changes. The underestimation noise was effectively corrected by the procedures such as the time-series correction considering vegetation phenology, the outlier removal using long-term climatology, and the gap filling using rigorous statistical methods. The correlation with MODIS NDVI was higher, and the difference was lower, showing a 32.7% improvement compared to the original NDVI product. The proposed method has an extensibility for use in other satellite products with some modification.