• Journal of Broadcast Engineering
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• v.18 no.2
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• pp.319-322
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• 2013

Image retrieval research activity has moved its focus from global descriptors to local descriptors of feature point such as SIFT. MPEG is Currently working on standardization of effective coding of location and local descriptors of feature point in the context mobile based image search driven application in the name of MPEG-7 CDVS (Compact Descriptor for Visual Search). The extracted feature points consist of two parts, location information and Descriptor. For efficient image retrieval, we proposed a novel method that is gradual block-based efficient lossy location coding to compress location information according to distribution in images. From experimental result, the number of average bits per feature point reduce 5~6% and the accuracy rate keep compared to state of the art TM 3.0.

• Journal of KIISE:Software and Applications
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• v.31 no.3
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• pp.379-386
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• 2004

Video segmentation is a fundamental task in video indexing and it includes two kinds of shot change detections such as the abrupt transition and the gradual transition. The abrupt shot boundaries are detected by computing the image-based distance between adjacent frames and comparing this distance with a pre-determined threshold value. However, the gradual shot boundaries are difficult to detect with this approach. To overcome this difficulty, we propose the method that detects gradual transition in the MPEG compressed video using the HMM (Hidden Markov Model). We take two different HMMs such as a discrete HMM and a continuous HMM with a Gaussian mixture model. As image features for HMM's observations, we use two distinct features such as the difference of histogram of DC images between two adjacent frames and the difference of each individual macroblock's deviations at the corresponding macroblock's between two adjacent frames, where deviation means an arithmetic difference of each macroblock's DC value from the mean of DC values in the given frame. Furthermore, we obtain the DC sequences of P and B frame by the first order approximation for a fast and effective computation. Experiment results show that we obtain the best detection and classification performance of gradual transitions when a continuous HMM with one Gaussian model is taken and two image features are used together.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1438-1443
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• 1999

In this paper, we propose detection methods for gradual scene changes such as dissolve, pan, and zoom. The proposal method to detect a dissolve region uses scene features based on spatial statistics of the image. The spatial statistics to define shot boundaries are derived from squared means within each local area. We also propose a method of the camera motion detection using four representative motion vectors in the background. Representative motion vectors are derived from macroblock motion vectors which are directly extracted from MPEG streams. To reduce the implementation time, we use DC sequences rather than fully decoded MPEG video. In addition, to detect the gradual scene change region precisely, we use all types of the MPEG frames(I, P, B frame). Simulation results show that the proposed detection methods perform better than existing methods.

• Journal of Information Processing Systems
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• v.14 no.2
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• pp.469-486
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• 2018

We propose an enhanced version of the local binary pattern (LBP) operator for texture extraction in images in the context of image retrieval. The novelty of our proposal is based on the observation that the LBP exploits only the lowest kind of local information through the global histogram. However, such global Histograms reflect only the statistical distribution of the various LBP codes in the image. The block based LBP, which uses local histograms of the LBP, was one of few tentative to catch higher level textural information. We believe that important local and useful information in between the two levels is just ignored by the two schemas. The newly developed method: gradual locality integration of binary patterns (GLIBP) is a novel attempt to catch as much local information as possible, in a gradual fashion. Indeed, GLIBP aggregates the texture features present in grayscale images extracted by LBP through a complex structure. The used framework is comprised of a multitude of ellipse-shaped regions that are arranged in circular-concentric forms of increasing size. The framework of ellipses is in fact derived from a simple parameterized generator. In addition, the elliptic forms allow targeting texture directionality, which is a very useful property in texture characterization. In addition, the general framework of ellipses allows for taking into account the spatial information (specifically rotation). The effectiveness of GLIBP was investigated on the Corel-1K (Wang) dataset. It was also compared to published works including the very effective DLEP. Results show significant higher or comparable performance of GLIBP with regard to the other methods, which qualifies it as a good tool for scene images retrieval.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.141-148
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• 2011

Most of the previous works on scene change detection algorithm focus on the detection of abrupt rather than gradual changes. In general, gradual scene change detection algorithms require heavy computation. Some of those approaches don't consider the error factors such as flashlights, camera or object movements, and special effects. Many scenes change detection algorithms based on the histogram show better performances than other approaches, but they have computation load problem. In this paper, we proposed a scene change detection algorithm with fast and accurate performance using the vertical and horizontal blocked slice images and their macro block informations. We apply graph cut partitioning algorithm for clustering and partitioning of video sequence using generated spatio-temporal histogram. When making spatio-temporal histogram, we only use the central block on vertical and horizontal direction for performance improvement. To detect camera and object movement as well as various special effects accurately, we utilize the motion vector and type information of the macro block.

• Journal of information and communication convergence engineering
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• v.15 no.3
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• pp.160-164
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• 2017

Public key cryptography (PKC) is the basic building block for the cryptography applications such as encryption, key distribution, and digital signature scheme. Among many PKC, elliptic curve cryptography (ECC) is the most widely used in IT systems. Recently, very efficient Montgomery-Twisted-Edward (MoTE)-ECC was suggested, which supports low complexity for the finite field arithmetic, group operation, and scalar multiplication. However, we cannot directly adopt the MoTE-ECC to new PKC systems since the cryptography is not fully evaluated in terms of performance on the Internet of Things (IoT) platforms, which only supports very limited computation power, energy, and storage. In this paper, we fully evaluate the MoTE-ECC implementations on the representative IoT devices (16-bit MSP processors). The implementation is highly optimized for the target platform and compared in three different factors (ROM, RAM, and execution time). The work provides good reference results for a gradual transition from legacy ECC to MoTE-ECC on emerging IoT platforms.

• Korean Journal of Remote Sensing
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• v.40 no.1
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• pp.9-18
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• 2024

Small streams, despite their rich ecosystems, face challenges in vegetation assessment due to the limitations of traditional, time-consuming methods. This study presents a groundbreaking approach, combining unmanned aerial vehicles(UAVs), convolutional neural networks(CNNs), and the vegetation differential vegetation index (VDVI), to revolutionize both assessment and management of stream vegetation. Focusing on Idong Stream in South Korea (2.7 km long, 2.34 km² basin area)with eight diverse revetment methods, we leveraged high-resolution RGB images captured by UAVs across five dates (July-December). These images trained a ResNeXt101 CNN model, achieving an impressive 89% accuracy in classifying vegetation cover(soil,water, and vegetation). This enabled detailed spatial and temporal analysis of vegetation distribution. Further, VDVI calculations on classified vegetation areas allowed assessment of vegetation vitality. Our key findings showcase the power of this approach:(a) TheCNN model generated highly accurate cover maps, facilitating precise monitoring of vegetation changes overtime and space. (b) August displayed the highest average VDVI(0.24), indicating peak vegetation growth crucial for stabilizing streambanks and resisting flow. (c) Different revetment methods impacted vegetation vitality. Fieldstone sections exhibited initial high vitality followed by decline due to leaf browning. Block-type sections and the control group showed a gradual decline after peak growth. Interestingly, the "H environment block" exhibited minimal change, suggesting potential benefits for specific ecological functions.(d) Despite initial differences, all sections converged in vegetation distribution trends after 15 years due to the influence of surrounding vegetation. This study demonstrates the immense potential of UAV-based remote sensing and CNNs for revolutionizing small-stream vegetation assessment and management. By providing high-resolution, temporally detailed data, this approach offers distinct advantages over traditional methods, ultimately benefiting both the environment and surrounding communities through informed decision-making for improved stream health and ecological conservation.

• Journal of Korea Multimedia Society
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• v.14 no.10
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• pp.1252-1261
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• 2011

In this paper, we propose the comparison method of pattern similarity for video segmentation algorithm. The shot boundary type is categorized as 2 types, abrupt change and gradual change. The representative examples of gradual change are dissolve, fade-in, fade-out or wipe transition. The proposed method consider the problem to detect shot boundary as 2-class problem. We concentrated if the shot boundary event happens or not. It is essential to define similarity between frames for shot boundary detection. We proposed 2 similarity measures, within similarity and between similarity. The within similarity is defined by feature comparison between frames belong to same shot. The between similarity is defined by feature comparison between frames belong to different scene. Finally we calculated the statistical patterns comparison between the within similarity and between similarity. Because this measure is robust to flash light or object movement, our proposed algorithm make contribution towards reducing false positive rate. We employed color histogram and mean of sub-block on frame image as frame feature. We performed the experimental evaluation with video dataset including set of TREC-2001 and TREC-2002. The proposed algorithm shows the performance, 91.84% recall and 86.43% precision in experimental circumstance.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.1
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• pp.72-81
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• 2019

Objective: To determine the effect of gut pH and rumen microbial fermentation on glycerol encapsulated in alginate and alginate-chitosan polymers. Methods: Glycerol was encapsulated at 2.5%, 5%, 7.5%, or 10% (w/w) with sodium alginate (A) and alginate-chitosan (AC) polymers. Surface morphology and chemical modifications of the beads were evaluated using scanning electron microscopy and Fourier transform infrared (FTIR) spectra. Encapsulation efficiency was determined at the 5% glycerol inclusion level in two experiments. In experiment 1, 0.5 g of alginate-glycerol (AG) and alginate-chitosan glycerol (ACG) beads were incubated for 2 h at $39^{\circ}C$ in pH 2 buffer followed by 24 h in pH 8 buffer to simulate gastric and intestinal conditions, respectively. In experiment 2, 0.5 g of AG and ACG beads were incubated in pH 6 buffer at $39^{\circ}C$ for 8 h to simulate rumen conditions. All incubations were replicated four times. Free glycerol content was determined using a spectrophotometer and used to assess loading capacity and encapsulation efficiency. An in vitro experiment with mixed cultures of rumen microbes was conducted to determine effect of encapsulation on microbial fermentation. Data were analyzed according to a complete block design using the MIXED procedure of SAS (SAS Institute, Cary, NC, USA). Results: For AG and ACG, loading capacity and efficiency were 64.7%, 74.7%, 70.3%, and 78.1%, respectively. Based on the FTIR spectra and scanning electron microscopy, ACG treatment demonstrated more intense and stronger ionic bonds. At pH 6, 36.1% and 29.7% of glycerol was released from AG and ACG, respectively. At pH 2 minimal glycerol was released but pH 8 resulted in 95.7% and 93.9% of glycerol released from AG and ACG, respectively. In vitro microbial data show reduced (p<0.05) fermentation of encapsulated glycerol after 24 h of incubation. Conclusion: The AC polymer provided greater protection in acidic pH with a gradual release of intact glycerol when exposed to an alkaline pH.

• Communications of Mathematical Education
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• v.25 no.3
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• pp.497-524
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• 2011

This study was to understand students' learning about the function of math combined with molecular motions of science using the block scheduling. It was based on the revised Class Structure Model of Lee et al.(2010) where MBL as a tool was used to increase students' participation and understanding in the integrated concepts. The researcher provided the 6th grade students who lived in Sung Nam-Si, Kyung Gi-Do with 8 unit lessons, consisting of 5 stages of CSM. As a result of the study, the integrated education of Mathematics and Science showed synergic effect in studying both subjects and brought a positive result in gradual mathematization. It may be hard to combine all the contents of mathematics and science together. However, learning the relation between volume and pressure, and between volume and temperature of gas used as an example of function shown in our daily life was appropriate through Fogarty's integrated education model because it supported the objective of both subjects. Also, it was a good idea to develop CSM because it was composed of the contents from both subjects held in the same period of a year. Through the five stages, students were able to establish and generalize the definitions and the concepts of function.