Eui-young Cha | Pusan National University (original) (raw)
Papers by Eui-young Cha
International Conference on Machine Learning and Applications, 2002
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1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227), 1998
Concerns the applications of fractal theory to image recognition and we propose the method that c... more Concerns the applications of fractal theory to image recognition and we propose the method that can enhance learning rate and recognition rate by using fractal parameters that are composed of input vectors for a neural network in an image recognition model. Fractal parameters with the properties of self-similarity and recursiveness can recover lossless original images through iterating processes. Therefore the original image can be implicitly represented and uniquely mapped by fractal parameters. The enhanced result is shown by computer simulations
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IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999
This paper describes a practical equation for estimating the fractal dimensions (FD) of images an... more This paper describes a practical equation for estimating the fractal dimensions (FD) of images and discusses the recognition model for which it is applicable. The FD is applied to pre-estimate quantities of the information that can be used to recognize images
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Lecture Notes in Computer Science, 2005
... 179-184 [6] Hansheng Lei, Srinivas Palla, Venu Govindaraju, ER²: An Intuitive Similarity Mea... more ... 179-184 [6] Hansheng Lei, Srinivas Palla, Venu Govindaraju, ER²: An Intuitive Similarity Measure for On-Line Signature Verification, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), October 2004 pp. ...
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International Journal of Multimedia and Ubiquitous Engineering, 2013
ABSTRACT Color information recognition methods based on the RGB color model, which is designed on... more ABSTRACT Color information recognition methods based on the RGB color model, which is designed on the basis of static fuzzy inference rules, are being widely used at present. However, these methods have certain limitations because of the nature of the model used: detachment of human vision and limited choice of environment. In this paper, we propose a method based on the HSI model and a new inference process that resembles the human vision recognition process. This method allows the user to add, delete, or update inference rules. In our method, membership intervals are designed with sine and cosine functions in the H channel and trigonometric style functions in the S and I channels. The membership degree is computed via an interval merging process. Then, inference rules are applied to the result in order to infer the color information. Experimental results show that our method is more intuitive and efficient than that based on the RGB model.
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WIT Transactions on State of the Art in Science and Engineering, 2011
ABSTRACT
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This paper presents a new method for container auto-landing system using stereo vision. The posit... more This paper presents a new method for container auto-landing system using stereo vision. The position estimation of the spreader is very important for improving the operating efficiency of the port. A central problem in estimation of container position is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we propose detection of container and estimation of distance from container to spreader using stereo vision. First, we extract region of container based on features in given a pair of stereo images. We detect lines of a container using Hough transform for extraction of morphological features. Then we extract candidate regions using crossing angle of straight lines. We segment the region of container using gray-labeling and perform experimental verification of geometric features. After that we match region of container based on area-based stereo matching approach. Through the process mentioned above, we get inform...
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In this paper, we propose a novel recognition method that extract source data from encoded signal... more In this paper, we propose a novel recognition method that extract source data from encoded signal that are displayed on FND mounted on home appliances. First of all, it find a candidate FND region from sequential difference images taken by smartphone and extract segment image using clustering RGB value. After that, it normalize segment images to correct a slant error and recognize each segments using a relative distance. Experiments show the robustness of the recognition algorithm on smartphone.
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In this paper, A lane tracking algoritm is proposed for lane departure warning system. To elimina... more In this paper, A lane tracking algoritm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Using clustering and lane similarity function with noise suppression features are extracted. Finally, lane model is calculated using RANSAC and lane model is tracked using Kalman Filter. Experimental results show that the proposed algorithm can be processed within 20ms and its detection rate approximately 90% on the highway in a variety of environments.
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International Conference on Machine Learning and Applications, 2002
Bookmarks Related papers MentionsView impact
1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227), 1998
Concerns the applications of fractal theory to image recognition and we propose the method that c... more Concerns the applications of fractal theory to image recognition and we propose the method that can enhance learning rate and recognition rate by using fractal parameters that are composed of input vectors for a neural network in an image recognition model. Fractal parameters with the properties of self-similarity and recursiveness can recover lossless original images through iterating processes. Therefore the original image can be implicitly represented and uniquely mapped by fractal parameters. The enhanced result is shown by computer simulations
Bookmarks Related papers MentionsView impact
IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339), 1999
This paper describes a practical equation for estimating the fractal dimensions (FD) of images an... more This paper describes a practical equation for estimating the fractal dimensions (FD) of images and discusses the recognition model for which it is applicable. The FD is applied to pre-estimate quantities of the information that can be used to recognize images
Bookmarks Related papers MentionsView impact
Lecture Notes in Computer Science, 2005
... 179-184 [6] Hansheng Lei, Srinivas Palla, Venu Govindaraju, ER²: An Intuitive Similarity Mea... more ... 179-184 [6] Hansheng Lei, Srinivas Palla, Venu Govindaraju, ER²: An Intuitive Similarity Measure for On-Line Signature Verification, Ninth International Workshop on Frontiers in Handwriting Recognition (IWFHR'04), October 2004 pp. ...
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International Journal of Multimedia and Ubiquitous Engineering, 2013
ABSTRACT Color information recognition methods based on the RGB color model, which is designed on... more ABSTRACT Color information recognition methods based on the RGB color model, which is designed on the basis of static fuzzy inference rules, are being widely used at present. However, these methods have certain limitations because of the nature of the model used: detachment of human vision and limited choice of environment. In this paper, we propose a method based on the HSI model and a new inference process that resembles the human vision recognition process. This method allows the user to add, delete, or update inference rules. In our method, membership intervals are designed with sine and cosine functions in the H channel and trigonometric style functions in the S and I channels. The membership degree is computed via an interval merging process. Then, inference rules are applied to the result in order to infer the color information. Experimental results show that our method is more intuitive and efficient than that based on the RGB model.
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Bookmarks Related papers MentionsView impact
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WIT Transactions on State of the Art in Science and Engineering, 2011
ABSTRACT
Bookmarks Related papers MentionsView impact
This paper presents a new method for container auto-landing system using stereo vision. The posit... more This paper presents a new method for container auto-landing system using stereo vision. The position estimation of the spreader is very important for improving the operating efficiency of the port. A central problem in estimation of container position is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we propose detection of container and estimation of distance from container to spreader using stereo vision. First, we extract region of container based on features in given a pair of stereo images. We detect lines of a container using Hough transform for extraction of morphological features. Then we extract candidate regions using crossing angle of straight lines. We segment the region of container using gray-labeling and perform experimental verification of geometric features. After that we match region of container based on area-based stereo matching approach. Through the process mentioned above, we get inform...
Bookmarks Related papers MentionsView impact
In this paper, we propose a novel recognition method that extract source data from encoded signal... more In this paper, we propose a novel recognition method that extract source data from encoded signal that are displayed on FND mounted on home appliances. First of all, it find a candidate FND region from sequential difference images taken by smartphone and extract segment image using clustering RGB value. After that, it normalize segment images to correct a slant error and recognize each segments using a relative distance. Experiments show the robustness of the recognition algorithm on smartphone.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact
In this paper, A lane tracking algoritm is proposed for lane departure warning system. To elimina... more In this paper, A lane tracking algoritm is proposed for lane departure warning system. To eliminate perspective effect, input image is converted into Bird's View by inverse perspective mapping. Next, suitable features are extracted for lane detection. Using clustering and lane similarity function with noise suppression features are extracted. Finally, lane model is calculated using RANSAC and lane model is tracked using Kalman Filter. Experimental results show that the proposed algorithm can be processed within 20ms and its detection rate approximately 90% on the highway in a variety of environments.
Bookmarks Related papers MentionsView impact
Bookmarks Related papers MentionsView impact