• Journal of IKEEE
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• v.22 no.1
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• pp.149-155
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• 2018

In this paper, we used ET(Electrical Tomography) for earth resistivity image reconstruction of vertical multi layer underground model. The earth resistivity is analyzed generally as the parallel multi-layer model, however possibly there happens vertical layer model. Here to find the best electrode array in case of vertical layer underground model, Wenner, Schlumberger, and Dipole-dipole electrode arrays, which are well known electrode arrays used in ET, have been tested. And Gauss-Newton algorithm is used in ET inversion. RMS error analysis shows that Wenner electrode array is best in imaging.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.99-112
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• 2015

Digital imaging technology has advanced beyond the limits of the multimedia industry IT convergence, and to develop a complex industry, particularly in the field of object recognition, face smart-phones associated with various Application technology are being actively researched. Recently, face recognition technology is evolving into an intelligent object recognition through image recognition technology, detection technology, the detection object recognition through image recognition processing techniques applied technology is applied to the IP camera through the 3D image object recognition technology Face Recognition been actively studied. In this paper, we first look at the essential human factor, technical factors and trends about the technology of the human object recognition based SPFACS(Smile Progress Facial Action Coding System)study measures the smile detection technology recognizes multi-faceted object recognition. Study Method: 1)Human cognitive skills necessary to analyze the 3D object imaging system was designed. 2)3D object recognition, face detection parameter identification and optimal measurement method using the AAM algorithm inside the proposals and 3)Face recognition objects (Face recognition Technology) to apply the result to the recognition of the person's teeth area detecting expression recognition demonstrated by the effect of extracting the feature points.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2737-2753
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• 2013

In this study, we propose a novel salient object detection strategy based on regional contrast and relative spatial compactness. Our algorithm consists of four basic steps. First, we learn color names offline using the probabilistic latent semantic analysis (PLSA) model to find the mapping between basic color names and pixel values. The color names can be used for image segmentation and region description. Second, image pixels are assigned to special color names according to their values, forming different color clusters. The saliency measure for every cluster is evaluated by its spatial compactness relative to other clusters rather than by the intra variance of the cluster alone. Third, every cluster is divided into local regions that are described with color name descriptors. The regional contrast is evaluated by computing the color distance between different regions in the entire image. Last, the final saliency map is constructed by incorporating the color cluster's spatial compactness measure and the corresponding regional contrast. Experiments show that our algorithm outperforms several existing salient object detection methods with higher precision and better recall rates when evaluated using public datasets.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.41 no.4
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• pp.39-43
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• 2004

A typical theme of active vision systems is gaze-fixing of a camera. Here gaze-fixing of a camera means by steering orientation of a camera so that a given point on the object is always at the center of the image. For this we need to combine a function to analyze image data and a function to control orientation of a camera. This paper presents an algorithm for gaze-fixing of a camera where image analysis and orientation control are designed in a frame. At this time, for avoiding difficulties in implementing and aiming for real-time applications we design the algorithm to be a simple closed-form without using my information related to calibration of the camera or structure estimation.

• The Transactions of the Korea Information Processing Society
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• v.4 no.10
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• pp.2553-2561
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• 1997

In this paper, a hardware architecture to calculate straight-line Hough transform algorithm for image recognition is suggested. This processor consists of the filtering module for gradient calculation and the HT calculation module, and the angle information are stored in memory table. For the suggested architecture, firstly, algorithm simulation is executed using C language to confirm the operation and to decide the precision of calculation, and secondly, architecture simulation is executed using VHDL language for the total blocks. According to C & VHDL simulation results, it is confirmed that the calculated data value is similarly obtained and the calculation defference is decreased as image clarity and bits increase.

• Journal of IKEEE
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• v.23 no.3
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• pp.978-983
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• 2019

Under the influence of Autonomous Driving and AI, it is important to accurately recognize and judge objects through cameras. In particular, since a method of recognizing an object using a camera can obtain a large amount of information visually compared to other methods, many image signal processing methods have been studied to extract an accurate image. In addition, a lot of research is being carried out to implementation about hardware. In this work, we compare the principles and characteristics of the sorting algorithms that are frequently used in image signal processing and summarize the performance evaluation. Based on this, we define an efficient algorithm when implemented in hardware among efficient sorting algorithms.

• Journal of Korea Multimedia Society
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• v.24 no.8
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• pp.1114-1121
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• 2021

In this paper, we implement a recipe recommendation system using ingredient harmonization analysis based on recipe data. The proposed system receives an image of a food ingredient purchase receipt to recommend ingredients and recipes to the user. Moreover, it performs preprocessing of the receipt images and text extraction using the OCR algorithm. The proposed system can recommend recipes based on the combined data of ingredients. It collects recipe data to calculate the combination for each food ingredient and extracts the food ingredients of the collected recipe as training data. And then, it acquires vector data by learning with a natural language processing algorithm. Moreover, it can recommend recipes based on ingredients with high similarity. Also, the proposed system can recommend recipes using replaceable ingredients to improve the accuracy of the result through preprocessing and postprocessing. For our evaluation, we created a random input dataset to evaluate the proposed recipe recommendation system's performance and calculated the accuracy for each algorithm. As a result of performance evaluation, the accuracy of the Word2Vec algorithm was the highest.

• Journal of the Korean Institute of Landscape Architecture
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• v.30 no.2
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• pp.1-11
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• 2002

The purpose of this study is to investigate landscape image and define elements of difference in visual preference of bridges on the Han River. To do this end, video was used as a media for the evaluation of the landscape image of 16 bridges on the Han River using a Semantic Differential scale. Data is collected by 50 students from Woosuk University, majoring landscape architecture. Final analysis utilized a total of 704 samples of data. Data is analyzed through descriptive statistics, and spatial image is analyzed by factor analysis algorithm Principle component analysis using Varimax method is applied far extraction and factor rotation. T-test is used to find the difference between the bridge type of preference with the data of factor score. Logistic regression is used to select the factors that influences the visual preference among the image factors. The results of this study can be summarized as follows; The image of whole bridges on the Han River is somewhat orderly, sequential and open. The degree of visual preference of unique bridge type is higher than normal but there are some differences in visual preference within the same type of structure. This suggests that the surrounding landscape is one of the important factor for visual preference. Factors covering the image of bridge are found to be 'aesthetic',　'structure','spatial factor', and 'shape'. Total variance is obtained as 60.4%. The aesthetic variables are the most important factor for visual preference and the structural factor presents no significant difference in visual preference between more preferred and less preferred bridges. Since the collapse of Songsu Bridge, we thought the structural factor is very important but the results of this study suggest that it is more important to consider the aesthetic and spatial factors of the bridge to increase the visual preference when planning and designing bridges. Simulations with more detailed data about surroundings should be utilized practical design.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.397-402
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• 2003

This paper proposes an efficient fixed-point (FP) algorithm for improving performances of the independent component analysis (ICA) based on neural networks. The proposed algorithm is the FP algorithm based on Newton method for ICA using the adaptive learning parameters. The purpose of this algorithm is to improve the separation speed and performance by using the learning parameters in Newton method, which is based on the first order differential computation of entropy optimization function. The learning rate and the moment are adaptively adjusted according to an updating state of inverse mixing matrix. The proposed algorithm has been applied to the fingerprints and the images generated by random mixing matrix in the 8 fingerprints of 256${\times}$256-pixel and the 10 images of 512$\times$512-pixel, respectively. The simulation results show that the proposed algorithm has the separation speed and performance better than those using the conventional FP algorithm based on Newton method. Especially, the proposed algorithm gives relatively larger improvement degree as the problem size increases.

• Journal of Satellite, Information and Communications
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• v.11 no.4
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• pp.1-9
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• 2016

This paper was studied in two ways with respect to the information received from the video signal separation technique of PPI Scop radar device. The proposed technique consists in generating an image signal through the video signal separation and synthesis, symbol generation, the residual image signal generation process. This technology can greatly improve the operating convenience with improved ease of discrimination, screen readability for the operator in analyzing radar information. The first proposed method was constructed for high-speed FPGA-based information processing systems for high speed operation stability of the system. The second proposed method was implemented intelligent algorithms and a software algorithm function curve associated resources.This was required to meet the constraints on the radar information, analysis system. Existing radar systems have not the frame data analysis unit image. However, this study was designed to image data stored in the frame-by-frame analysis of radar images with express information MPEG4 video. Key research content is to highlight the key observations expresses the target, the object-specific monitoring information to the positive image processing algorithm and the function curve delays. For high-definition video, high-speed to implement data analysis and expressing a variety of information was applied to the ARM Processor Support in Pro ASIC3.