• Journal of Institute of Control, Robotics and Systems
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• v.16 no.7
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• pp.674-680
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• 2010

It is known that many insects and animals can return to their nest after exploration, with their own specific homing mechanisms. Their homing navigation methods have been applied to the robotic navigation. In this paper, we test the sector-based image matching method motivated by the honeybee's landmark navigation behaviour. Here, our robotic approach uses the reference compass to identify the current head direction and the relative angular position of landmarks for the navigation. The robot shows desirable homing behaviors if the robot is surrounded by landmarks. The result of robot experiment is in good agreement with that of simulation.

• The KIPS Transactions:PartB
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• v.16B no.3
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• pp.195-202
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• 2009

In this paper, we propose the regions segmentation method of the white matter and the gray matter for brain MR image by using the ant colony optimization algorithm. Ant Colony Optimization (ACO) is a new meta heuristics algorithm to solve hard combinatorial optimization problem. This algorithm finds the expected pixel for image as the real ant finds the food from nest to food source. Then ants deposit pheromone on the pixels, and the pheromone will affect the motion of next ants. At each iteration step, ants will change their positions in the image according to the transition rule. Finally, we can obtain the segmentation results through analyzing the pheromone distribution in the image. We compared the proposed method with other threshold methods, viz. the Otsu' method, the genetic algorithm, the fuzzy method, and the original ant colony optimization algorithm. From comparison results, the proposed method is more exact than other threshold methods for the segmentation of specific region structures in MR brain image.

• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.1-11
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• 2009

To classifying and filtering of adult images, in recent the computer vision techniques are actively investigated because rapidly increase for the amount of adult images accessible on the Internet. In this paper, we investigate and develop the tool filtering of adult images using skin color model. The tool is consisting of two steps. In the first step, we use a skin color classifier to extract skin color regions from an image. In the nest step, we use a region feature classifier to determine whether an image is an adult image or not an adult image depending on extracted skin color regions. Using histogram color model, a skin color classifier is trained for RGB color values of adult images and not adult images. Using SVM, a region feature classifier is trained for skin color ratio on 29 regions of adult images. Experimental results show that suggested classifier achieve a detection rate of 92.80% with 6.73% false positives.

• Imaging Science in Dentistry
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• v.31 no.1
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• pp.1-7
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• 2001

Purpose : To evaluate the usefulness of the reconstructed 3-dimensional image on the personal computer in comparison with that of the CT workstation by quantitative comparison and analysis. Materials and Methods : The spiral CT data obtained from 27 persons were transferred from the CT workstation to a personal computer, and they were reconstructed as 3-dimensional image on the personal computer using V-works 2.0/sup TM/. One observer obtained the 14 measurements on the reconstructed 3-dimensional image on both the CT workstation and the personal computer. Paired Nest was used to evaluate the intraobserver difference and the mean value of the each measurement on the CT workstation and the personal computer. Pearson correlation analysis and % incongruence were also performed. Results: I-Gn, N-Gn, N-A, N-Ns, B-A, and G-Op did not show any statistically significant difference (p>0.05), B-O, B-N, Eu-Eu, Zy-Zy, Biw, D-D, Orbrd R, and L had statistically significant difference (p<0.05), but the mean values of the differences of all measurements were below 2 mm, except for D-D. The value of correlation coefficient y was greater than 0.95 at I-Gn, N-Gn, N-A, N-Ns, B-A, B-N, G-Op, Eu-Eu, Zy-Zy, and Biw, and it was 0.75 at B-O, 0.78 at D-D, and 0.82 at both Orbrd Rand L. The % incongruence was below 4% at I-Gn, N-Gn, N-A, N-Ns, B-A, B-N, G-Op, Eu-Eu, Zy-Zy, and Biw, and 7.18%, 10.78%, 4.97%, 5.89% at B-O, D-D, Orbrd Rand L respectively. Conclusion : It can be considered that the utilization of the personal computer has great usefulness in reconstruction of the 3-dimensional image when it comes to the economics, accessibility and convenience, except for thin bones and the landmarks which are difficult to be located.

• Lingua Humanitatis
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• v.2 no.2
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• pp.349-362
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• 2002

The paper argues for the necessicity of revising many fundamental concepts that we use in everyday situations and in communication such as reality, thought, language, the world and finally the truth. The paper develops the argument that what the word ′truth′ actually signifies cannot be addressed just by explicating what philosophy, science or even religion denote but that it can only be answered fully by the study of language and therefore in a larger context linguistics. Language is the very tool that enriches the communication between one another due to its diverse significations that one may use when expressing one′s views, thereby making life more enjoyable. The paper develops why the above corresponding argument should be justified by developing three outstanding views as follows. The world or reality is indistinguishable from the common worldview that we associate with without the means of language. That the worldview is in essence inseparable from the mental and intellectual representation of it and the only means of expression lies with language. And finally, that the language is a complex signification in itself in every aspect. Language in short is the very essence of what we define as being ′poetic.′ With these arguments in mind, we may once again ponder the signification of Nietzsche′s words when he states that "to see science through the lens of art, and art through the lens of life."