• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.9 no.4
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• pp.414-418
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• 2016

In this paper, a hardware architecture of low area gradient magnitude calculator is proposed. For the hardware complexity reduction, the characteristic of orthogonal projection vector and hardware resource sharing technique are applied. The proposed hardware architecture can be implemented without degradation of the gradient magnitude data quality since the proposed hardware is implemented with original algorithm. The FPGA implementation result shows the 15% of logic elements and 38% embedded multiplier savings compared with previous work using Altera Cyclone VI (EP4CE115F29C7N) FPGA and Quartus II v15.0 environment.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.4
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• pp.422-433
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• 2001

In this paper, we propose a flew edge detection method based on water flow model, in which gradient image surface is considered as a 3-dimensional (3-D) geographical feature. The edges of the objects in the background can be detected by the large gradient magnitude areas and to make the edges immersed it is required to invert the gradient image. The proposed edge detector uses a water flow model based enhancement and locally adaptive thresholding technique applied to the inverted gradient image resulting in better noise performance. Computer simulations with a few synthetic and real images show that the Proposed method can extract edge contour effectively.

• Journal of Distribution Science
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• v.13 no.5
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• pp.5-14
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• 2015

Purpose - Loyalty programs enable retailers to maintain longer and better customer relationships. In successful services, customers actively use and value these programs. As the proximity to the goal (goal gradient) might signal active participation, this study empirically examines customer's goal gradient behavior in a multi-vendor loyalty program. We also consider the effect of customer's accrual diversity on goal gradients, which is a differentiating feature in a multi-vendor loyalty program, and is further examined. Research Design, Data, and Methodology - The data consists of6,646 OK Cashbag members' individual transaction records from 2006 to 2009. The goal gradient hypothesis was tested as an increase in both the speed and the amount of accumulated award points. Result - The findings suggest that the goal gradient is also observed in a multi-vendor loyalty program, occurring more strongly among members with high accrual diversity. Conclusions - The results indicate that customers with high accrual diversity attend strongly to goal gradients in multi-vendor loyalty programs; hence, it is important for such program managers to better inform members about affiliated partners.

• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.321-335
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• 2021

Particulate matter (PM10 and PM2.5 with a diameter less than 10 and 2.5 ㎛, respectively) can be absorbed by the human body and adversely affect human health. Although most of the PM monitoring are based on ground-based observations, they are limited to point-based measurement sites, which leads to uncertainty in PM estimation for regions without observation sites. It is possible to overcome their spatial limitation by using satellite data. In this study, we developed machine learning-based retrieval algorithm for ground-level PM10 and PM2.5 concentrations using aerosol parameters from Geostationary Ocean Color Imager (GOCI) satellite and various meteorological parameters from a numerical weather prediction model during January to December of 2019. Gradient Boosted Regression Trees (GBRT) and Light Gradient Boosting Machine (LightGBM) were used to estimate PM concentrations. The model performances were examined for two types of feature sets-all input parameters (Feature set 1) and a subset of input parameters without meteorological and land-cover parameters (Feature set 2). Both models showed higher accuracy (about 10 % higher in R2) by using the Feature set 1 than the Feature set 2. The GBRT model using Feature set 1 was chosen as the final model for further analysis(PM10: R2 = 0.82, nRMSE = 34.9 %, PM2.5: R2 = 0.75, nRMSE = 35.6 %). The spatial distribution of the seasonal and annual-averaged PM concentrations was similar with in-situ observations, except for the northeastern part of China with bright surface reflectance. Their spatial distribution and seasonal changes were well matched with in-situ measurements.

• IEMEK Journal of Embedded Systems and Applications
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• v.4 no.4
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• pp.190-194
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• 2009

Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. Because high-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system with iris feature extraction methods based on USN(Ubiquitous Sensor Network). Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

• Journal of information and communication convergence engineering
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• v.2 no.3
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• pp.177-181
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• 2004

In this paper, we suggest an Iris recognition system with an excellent recognition rate and confidence as an alternative biometric recognition technique that solves the limit in an existing individual discrimination. For its implementation, we extracted coefficients feature values with the wavelet transformation mainly used in the signal processing, and we used neural network to see a recognition rate. However, Scale Conjugate Gradient of nonlinear optimum method mainly used in neural network is not suitable to solve the optimum problem for its slow velocity of convergence. So we intended to enhance the recognition rate by using Levenberg-Marquardt Back-propagation which supplements existing Scale Conjugate Gradient for an implementation of the iris recognition system. We improved convergence velocity, efficiency, and stability by changing properly the size according to both convergence rate of solution and variation rate of variable vector with the implementation of an applied algorithm.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.15-21
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• 2011

This paper proposes a new approach to palmprint verification based on the gradient, in which a palm image is considered to be a three-dimensional terrain. Principal lines and wrinkles make deep and shallow valleys on a palm landscape. Then the steepest slope direction in each local area is first computed using the Kirsch operator, after which an orientation map is created that represents the dominant slope direction of each pixel. In this study, three orientation maps were made with different scales to represent local and global gradient information. Next, feature matching based on pixel-unit comparison was performed. The experimental results showed that the proposed method is superior to several state-of-the-art methods. In addition, the verification could be greatly improved by fusing orientation maps with different scales.

• Journal of Sensor Science and Technology
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• v.27 no.6
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• pp.374-379
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• 2018

The piezocomposite transducer is widely used because it is highly efficient in transforming electric energy into mechanical energy, and its frequency range is broader than that of other types of ultrasound transducers. A general piezocomposite transducer is composed of an acoustic lens, impedance matching layers, piezoelectric materials, and backing layers. When an input voltage is applied to a piezoelectric material as an active material, it generates sound waves while vibrating. At that time, an impedance matching layer helps the sound waves to propagate forward while reducing the impedance mismatch that may occur at the interface between the active material and its front material. The impedance mismatch has a negative effect on the signal of an ultrasound transducer; thus, it is important to design a matching layer to overcome the issue. In this study, an optimized feature of a matching layer with gradient properties is studied. An objective function is defined to minimize both the average and the deviation of the reflection coefficients that are functions of the frequencies. As a result, an improvement in the signal characteristics with respect to the sensitivity and bandwidth is reported.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.300-311
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• 2014

According to fast change of the environment, the structured study of the ecosystem by analyzing the plant leaves are needed. Expecially, the methodology that searches and classifies the leaves from captured from the smart device have received numerous concerns in the field of computer science and ecology. In this paper, we propose a plant leaf classification technique using shape descriptor by combining Scale Invarinat Feature Transform (SIFT) and Histogram of Oriented Gradient (HOG) from the image segmented from the background via Graphcut algorithm. The shape descriptor is coded in the field of Locality-constrained Linear Coding to optimize the meaningful features from a high degree of freedom. It is connected to Support Vector Machines (SVM) for efficient classification. The experimental results show that our proposed approach is very efficient to classify the leaves which have similar color, and shape.

• Journal of KIISE:Software and Applications
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• v.32 no.6
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• pp.570-579
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• 2005

Facial expression recognition technology that has potentialities for applying various fields is appling on the man-machine interface development, human identification test, and restoration of facial expression by virtual model etc. Using sequential facial images, this study proposes a simpler method for detecting human facial expressions such as happiness, anger, surprise, and sadness. Moreover the proposed method can detect the facial expressions in the conditions of the sequential facial images which is not rigid motion. We identify the determinant face and elements of facial expressions and then estimates the feature regions of the elements by using information about color, size, and position. In the next step, the direction patterns of feature regions of each element are determined by using optical flows estimated gradient methods. Using the direction model proposed by this study, we match each direction patterns. The method identifies a facial expression based on the least minimum score of combination values between direction model and pattern matching for presenting each facial expression. In the experiments, this study verifies the validity of the Proposed methods.