• Journal of the Institute of Electronics Engineers of Korea SD
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• v.40 no.1
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• pp.45-51
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• 2003

JPEG200, a new international standard for still image compression based on wavelet and bit-plane coding techniques, is developed. In this paper, we design the DWT(Discrete Wavelet Transform) and quantizer for JPEG2000 CODEC. DWT handles both lossy and lossless compression using the same transform-based framework: The Daubechies 9/7 and 5/3 transforms, and quantizer is implemented as SQ(Scalar Quantization). The architecture of the proposed DWT and SQ are synthesized and verified using Xilinx FPGA technology. It operates up to 30MHz, and executes algorithms of wavelet transform and quantization for VGA 10 frame per second.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.5
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• pp.485-492
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• 2012

Today, a digital airborne imaging sensor plays an important role in construction of the numerous National Spatial Data Infrastructure. However, an appropriate quality assesment procedure for the acquired digital images should be preceded to make them useful data with high precision and reliability. A lot of studies therefore have been conducted in attempt to assess quality of digital images at home and abroad. In this regard, many test fields have been already established and operated to calibrate digital photogrammetric airborne imaging systems in Europe and America. These test fields contain not only GCPs(Ground Control Points) to test geometric performance of a digital camera but also various types of targets to evaluate its spatial and radiometric resolution. The purpose of this paper is to present a method to verify the spatial resolution of the Intergraph DMC digital camera and its results based on an experimental field testing. In field test, a simple bar target to be easily identified in image is used to check the spatial resolution. Images, theoretically designed to 12cm GSD(Ground Sample Distance), were used to calculate the actual resolution for all sub-images and virtual images in flight direction as well as in cross flight direction. The results showed that the actual image resolution was about 0.6cm worse than theoretically expected resolution. In addition, the greatest difference of 1.5cm between them was found in the image of block edge.

• Journal of Broadcast Engineering
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• v.21 no.3
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• pp.341-348
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• 2016

HEVC is the next compression standard and is expected to be used widely replacing the conventional H.264/AVC standard. The compression ratio of the HEVC is twice times than H.264/AVC, whereas its computational complexity is increased by up to 40%. Many research efforts have been made to reduce the computational complexity and to speed up encoding. For intra coding, the rough mode decision (RMD) is commonly applied. The rate-distortion optimization (RDO) process to decide the best mode is too complex so that RMD chooses the candidate modes with a simple process and sends the candidates to RDO process. However, for large-size blocks, the RMD also requires considerable computations. In this paper, a down-sampling scheme is proposed for the RMD process. The reference pixel loading, predicted pixel generation are performed using the down-sampled pixel data. When the proposed scheme is applied to the RMD, the computational complexity is reduced by 70% with a marginal bitrate increase of 0.04%. In terms of area of hardware-based RMD, the gate count and the buffer size is reduced 33% and 66%, respectively.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.713-722
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• 2013

This paper proposes a method of using depth information to detect the hand region in real-time based on the cascade method. In order to ensure stable and speedy detection of the hand region even under conditions of lighting changes in the test environment, this study uses only features based on depth information, and proposes a method of detecting the hand region by means of a classifier that uses boosting and cascading methods. First, in order to extract features using only depth information, we calculate the difference between the depth value at the center of the input image and the average of depth value within the segmented block, and to ensure that hand regions of all sizes will be detected, we use the central depth value and the second order linear model to predict the size of the hand region. The cascade method is applied to implement training and recognition by extracting features from the hand region. The classifier proposed in this paper maintains accuracy and enhances speed by composing each stage into a single weak classifier and obtaining the threshold value that satisfies the detection rate while exhibiting the lowest error rate to perform over-fitting training. The trained classifier is used to classify the hand region, and detects the final hand region in the final merger stage. Lastly, to verify performance, we perform quantitative and qualitative comparative analyses with various conventional AdaBoost algorithms to confirm the efficiency of the hand region detection algorithm proposed in this paper.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.