• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.575-580
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• 2010

Eye gaze as a form of input was primarily developed for users who are unable to use usual interaction devices such as keyboard and the mouse; however, with the increasing accuracy in eye gaze detection with decreasing cost of development, it tends to be a practical interaction method for able-bodied users in soon future as well. This paper explores a low-cost, robust, rotation and illumination independent eye gaze system for gaze enhanced user interfaces. We introduce two brand-new algorithms for fast and sub-pixel precise pupil center detection and 2D Eye Gaze estimation by means of deformable template matching methodology. In this paper, we propose a new algorithm based on the deformable angular integral search algorithm based on minimum intensity value to localize eyeball (iris outer boundary) in gray scale eye region images. Basically, it finds the center of the pupil in order to use it in our second proposed algorithm which is about 2D eye gaze tracking. First, we detect the eye regions by means of Intel OpenCV AdaBoost Haar cascade classifiers and assign the approximate size of eyeball depending on the eye region size. Secondly, using DAISMI (Deformable Angular Integral Search by Minimum Intensity) algorithm, pupil center is detected. Then, by using the percentage of black pixels over eyeball circle area, we convert the image into binary (Black and white color) for being used in the next part: DTBGE (Deformable Template based 2D Gaze Estimation) algorithm. Finally, using DTBGE algorithm, initial pupil center coordinates are assigned and DTBGE creates new pupil center coordinates and estimates the final gaze directions and eyeball size. We have performed extensive experiments and achieved very encouraging results. Finally, we discuss the effectiveness of the proposed method through several experimental results.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.8
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• pp.3312-3327
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• 2020

Plant diseases are a significant yield and quality constraint for farmers around the world due to their severe impact on agricultural productivity. Such losses can have a substantial impact on the economy which causes a reduction in farmer's income and higher prices for consumers. Further, it may also result in a severe shortage of food ensuing violent hunger and starvation, especially, in less-developed countries where access to disease prevention methods is limited. This research presents an investigation of Directional Local Quinary Patterns (DLQP) as a feature descriptor for plants leaf disease detection and Support Vector Machine (SVM) as a classifier. The DLQP as a feature descriptor is specifically the first time being used for disease detection in horticulture. DLQP provides directional edge information attending the reference pixel with its neighboring pixel value by involving computation of their grey-level difference based on quinary value (-2, -1, 0, 1, 2) in 0°, 45°, 90°, and 135° directions of selected window of plant leaf image. To assess the robustness of DLQP as a texture descriptor we used a research-oriented Plant Village dataset of Tomato plant (3,900 leaf images) comprising of 6 diseased classes, Potato plant (1,526 leaf images) and Apple plant (2,600 leaf images) comprising of 3 diseased classes. The accuracies of 95.6%, 96.2% and 97.8% for the above-mentioned crops, respectively, were achieved which are higher in comparison with classification on the same dataset using other standard feature descriptors like Local Binary Pattern (LBP) and Local Ternary Patterns (LTP). Further, the effectiveness of the proposed method is proven by comparing it with existing algorithms for plant disease phenotyping.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.67-73
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• 2010

In this paper, a new face detection method that is more accurate than the conventional methods is proposed. This method utilizes a hybrid of Hausdorff distance based on the geometric similarity between the two sets of points and the LBP distance based on the distribution of local micro texture of an image. The parameters for normalization and the optimal blending factor of the two different metrics were calculated from training sample images. Popularly used face database was used to show that the proposed method is more effective and robust to the variation of the pose, illumination, and back ground than the methods based on the Hausdorff distance or LBP distance. In the particular case, the average error distance between the detected and the true face location was reduced to 47.9% of the result of LBP method, and 22.8% of the result of Hausdorff method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.830-833
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• 2007

In this paper, we implemented a $17{\times}17b$ binary digital multiplier using radix-4 Booth;s algorithmand proposed an efficient testing methodology for the full-custom design. A two-stage pipeline architecture was applied to achieve higher throughput and 4:2 adders were used for regular layout structure in the Wallace tree partition. Several chips were fabricated using LG Semicon 0.6-um 3-Metal N-well CMOS technology. We did fault simulations efficiently using the proposed test method resulting in the reduction of the number of faulty nodes by 88%. The chip contains 9115 transistors and the core area occupies $1135^*1545$ mm2. The functional tests using ATS-2 tester showed that it can operate with 24 MHz clock at 5.0 V at room temperature.

• Journal of KIISE
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• v.45 no.1
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• pp.22-29
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• 2018

Over the decades, neural networks have been successfully used in numerous applications from speech recognition to image classification. However, these neural networks cannot explain their results and one needs to know how and why a specific conclusion was drawn. Most studies focus on extracting binary rules from neural networks, which is often impractical to do, since data sets used for machine learning applications contain continuous values. To fill the gap, this paper presents an algorithm to extract logic rules from a trained neural network for data with continuous attributes. It uses hyperplane-based linear classifiers to extract rules with numeric values from trained weights between input and hidden layers and then combines these classifiers with binary rules learned from hidden and output layers to form non-linear classification rules. Experiments with different datasets show that the proposed approach can accurately extract logical rules for data with nonlinear continuous attributes.

• Journal of IKEEE
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• v.24 no.1
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• pp.225-231
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• 2020

In this paper, we propose a method to accelerate BWN based on FPGA with limited resources for embedded system. Because of the limited number of logic elements available, a single computing unit capable of handling Conv-layer, FC-layer of various sizes must be designed and reused. Also, if the input feature map can not be parallel processed at one time, the output must be calculated by reading the inputs several times. Since the number of available BRAM modules is limited, the number of data bits in the BWN accelerator must be minimized. The image classification processing time of the BWN accelerator is superior when compared with a embedded CPU and is faster than a desktop PC and 50% slower than a GPU system. Since the BWN accelerator uses a slow clock of 50MHz, it can be seen that the BWN accelerator is advantageous in performance versus power.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.11
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• pp.111-118
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• 1990

In this paper, pSDF-based referance image is realized. Using BJTC (binary joint transform correlator) as the spatial plane correlator, optical pattern recognition for interclass identification and interclass discrimination is performed. Computer simulation shows that the correlation performance of BJTC is superior to that of JTC. Experimental results using BJTC reveal that correlation peak intensity is constant within the error rang from $4.1{\%}\to\9.6{\%}$ in interclass identification and correlation peak intensity of one class is two times higher than that of the other class in interclass discrimination, which indicates its superiority in discrimination sensitivity.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.27-32
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• 2005

An effective video watermarking algorithm is proposed to protect the copyright. The watermarking procedure is based on a three-dimensional discrete wavelet transform (3D DWT) and spread spectrum sequences. Two perceptual binary watermarks are preprocessed using mixing and pseudorandom permutation. After dividing the video sequence into video shots, the 3D DWT is performed, then the preprocessed watermarks are embedded into the 3D DWT coefficients, while considering robustness and invisibility, using two spread spectrum sequences defined as the user key. Experimental results show that the watermarked frames are subjectively indistinguishable from the original frames, plus the proposed video watermarking algorithm is sufficiently robust against such attacks as low pass filtering, frame dropping, frame average, and MPEG coding.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.595-597
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• 2015

LMC X-4 is an eclipsing high-mass X-ray binary exhibiting a superorbital modulation with a period of ~ 30:5 days. We present a detailed study of the variations of the superorbital modulation period with a time baseline of ~ 18 years. The period determined in the light curve collected by the Monitor of All-sky X-ray Image (MAXI) significantly deviates from that observed by the All Sky Monitor (ASM) onboard the Rossi X-ray Timing Explorer (RXTE). Using the data collected by RXTE/ASM, MAXI, and the Burst Alert Telescope (BAT) onboard Swift, we found a significant period derivative, $\dot{P}=(2.08{\pm}0.12){\times}10^{-5}$. Furthermore, the O{C residual shows complex short-term variations indicating that the superorbital modulation of LMC X-4 exhibits complicated unstable behaviors. In addition, we used archive data collected by the Proportional Counter Array (PCA) on RXTE to estimate the orbital and spin parameters. The detected pulse frequencies obtained in small time segments were fitted with a circular orbital Doppler shift model. In addition to orbital parameters and spin frequency for each observation, we found a spin frequency derivative of $\dot{v}=(6.482{\pm}0.011){\times}10^{-13}Hz{\cdot}s^{-1}$. More precise orbital and spin parameters will be evaluated by the pulse arrival time delay technique in the future.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.5
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• pp.1145-1153
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• 2013

Android mobile platform copy the class files of all applications installed in android platform and keep them into one directory. But to add the service library into a platform, Android must generate a new binary image of platform and replace the platform because android refer the libraries using the memory-mapped file method in a directory. And this memory-mapped file reference method waste the storage space of mobile device because that directory include the duplicated libraries if the libraries refered by application are duplicated, Therefore a dynamic reconfiguration method on android mobile platform is needed to manage the service libraries of application executed on android platform and support the version management and function addition/modification. In this paper, we propose the platform dynamic reconfiguration method to add dynmically the service libraries on android platform.