• Journal of Korea Multimedia Society
• /
• v.7 no.12
• /
• pp.1657-1664
• /
• 2004

We propose a method that classifies images into two object types man-made and natural objects. A central object is extracted from each image by using central object extraction method[1] before classification. A central object in an images defined as a set of regions that lies around center of the image and has significant color distribution against its surrounding. We define three measures to classify the object images. The first measure is energy of edge direction histogram. The energy is calculated based on the direction of only non-circular edges. The second measure is an energy difference along directions in Gabor filter dictionary. Maximum and minimum energy along directions in Gabor filter dictionary are selected and the energy difference is computed as the ratio of the maximum to the minimum value. The last one is a shape of an object, which is also represented by Gabor filter dictionary. Gabor filter dictionary for the shape of an object differs from the one for the texture in an object in which the former is computed from a binarized object image. Each measure is combined by using majority rule tin which decisions are made by the majority. A test with 600 images shows a classification accuracy of 86%.

• Journal of Software Engineering Society
• /
• v.29 no.1
• /
• pp.13-21
• /
• 2020

As CNN model is applied to various domains such as image classification and object detection, the performance of CNN model which is used to safety critical system like autonomous vehicles should be reliable. To evaluate that CNN model can sustain the performance in various environments, we developed an image data augmentation apparatus which generates images that is changed background. If an image which contains object is entered into the apparatus, it extracts an object image from the entered image and generate s composed images by synthesizing the object image with collected background images. A s a method to evaluate a CNN model, the apparatus generate s new test images from original test images, and we evaluate the CNN model by the new test image. As a case study, we generated new test images from Pascal VOC2007 and evaluated a YOLOv3 model with the new images. As a result, it was detected that mAP of new test images is almost 0.11 lower than mAP of the original test images.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.12 no.2
• /
• pp.189-197
• /
• 2012

It is usual for test data generation to be performed using either high-level specifications or source codes written in high-level programming languages. In certain circumstances, however, such information is not always available. This paper presents a technique that generates test data based on executable object codes. The proposed technique makes use of a very simple function minimization technique without sophisticated object code analysis and produces test data dynamically. We have conducted a simple experiment to evaluate the effectiveness of the proposed test data generation technique with a triangle classification program to show that branch coverage can be easily achieved.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.63 no.5
• /
• pp.703-712
• /
• 2014

To improve the efficiency and safety of railway systems, the train control system has been considerably evolved from the ground-equipment-based control system (e.g. track circuit, interlocking system, etc.) into the on-board-equipment-based control system. In addition, this train control system enables the rolling stock to intelligently control the trackside facilities by introducing the information and communication technologies (ICT). Accordingly, since the ICT-based train control system makes the railway system be simplified (i.e. the heavy ground-equipment can be removed), the efficient and cost-effective railway system can be realized. In this paper, we perform the feasibility test of the ICT-based train control system via a simulation. To this end, we have developed the prototypes of the on-board controller and wayside object control units which control the point and crossing gate and performed the integrated operation simulation in a testbed. In this paper, before the field test of the on-board-controller-based train control system, we perform the Consecutive operation test for prototypes of the on-board controller, wayside object control units and local control computer.

• International Journal of Precision Engineering and Manufacturing
• /
• v.5 no.3
• /
• pp.54-61
• /
• 2004

This paper describes the development of a 6-axis robot's finger force/moment sensor, which measures forces $F_x$(x-direction force), $F_y$and $F_z$, and moments $M_x$ (x-direction moment), $M_y$ and $M_z$ simultaneously, for stable grasping of an unknown object. In order to safely grasp an unknown object using the robot's gripper, the force in the gripping direction and the force in the gravity direction should be measured, and the force control should be performed using the measured forces. Also, the moments $M_x$, $M_y$ and $M_z$ to accurately perceive the position of the object in the grippers should be detected. Thus, the robot's gripper should be composed of 6-axis robot's finger force/moment sensor that can measure forces $F_x$, $F_y$ and $F_z$, and moments $M_x$ $M_y$ and $M_z$ simultaneously. In this paper, the 6-axis robot's finger force/moment sensor for measuring forces $F_x$, $F_y$ and $F_z$, and moments $M_x$ $M_y$ and $M_z$ simultaneously was newly modeled using several parallel-plate beams, designed, and fabricated. The characteristic test of the fabricated sensor was performed, and the result shows that interference errors of the developed sensor are less than 3%. Also, Robot's gripper with the 6-axis robot's finger force/moment sensor for the characteristic test of force control was manufactured, and the characteristic test for grasping an unknown object using the sensors was performed using it. The fabricated gripper could grasp an unknown object stably. Thus, the developed 6-axis robot's finger force/moment sensor can be used for robot's gripper.

• The Journal of Information Systems
• /
• v.10 no.1
• /
• pp.97-126
• /
• 2001

Object-orientation has been proposed as a promising software process innovation to improve software productivity and quality. It has not been understood clearly, however, what factors influences the diffusion of object-oriented technology in organizations. A research model was formulated and hypotheses were generated based on the literature of information technology implementation and software process innovation. To test the research hypotheses, a questionnaire survey was conducted. The results based on 121 responses from Korean companies revealed that project characteristics, use of external experts, and number of development projects are significantly related to the diffusion of object-oriented analysis and design and object-oriented programming. Innovation champion is positively related to the diffusion of object-oriented analysis and design, whereas it is not related to the diffusion of object-oriented programming language. Only project complexity was significantly related to the diffusion of visual programming language. On the other hand, organizational size was not significantly related to any object-oriented technology in this study.

• Proceedings of the IEEK Conference
• /
• 2003.07e
• /
• pp.2407-2410
• /
• 2003

In this paper, we propose a new stereoscopic video conversion methodology that converts two-dimensional (2-D) MPEG-4 video to stereoscopic video. In MPEG-4, each Image is composed of background object and primary object. In the first step of the conversion methodology, the camera motion type is determined for stereo Image generation. In the second step, the object-based stereo image generation is carried out. The background object makes use of a current image and a delayed image for its stereo image generation. On the other hand, the primary object uses a current image and its horizontally-shifted version to avoid the possible vertical parallax that could happen. Furthermore, URFA(Uncovered Region Filling Algorithm) is applied in the uncovered region which might be created after the stereo image generation of a primary object. In our experiment, show MPEG-4 test video and its stereoscopic video based upon out proposed methodology and analyze Its results.

• The Transactions of the Korea Information Processing Society
• /
• v.7 no.5
• /
• pp.1570-1578
• /
• 2000

Object motion is an important feature of content in video sequences. By now, various methods to exact feature about the object motion have been reported[1,2]. However they are not suitable to index video using the motion, since a lot of bits and complex indexing parameters are needed for the indexing [3,4] In this paper, we propose object motion map which could provide efficient indexing method for object motion. The proposed object motion map has both global and local motion information during an object is moving. Furthermore, it requires small bit of memory for the indexing. to evaluate performance of proposed indexing technique, experiments are performed with video database consisting of MPEG-1 video sequence in MPEG-7 test set.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2023.05a
• /
• pp.251-252
• /
• 2023

As technology improves with the 4th industrial revolution, smart construction is becoming a key part of safety management in the architecture and civil engineering. By using object detection technology with CCTV data, construction sites can be managed efficiently. In this study, super resolution technology based on deep learning is proposed to improve the accuracy of object detection in construction sites. As the resolution of a train set data and test set data get higher, the accuracy of object detection model gets better. Therefore, according to the scale of construction sites, different object detection models can be considered.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.2
• /
• pp.88-92
• /
• 2011

This paper looks at the development of the visual system of robots, and the development of image processing algorism to measure the size of an object and the distance from robot to an object for the visual system. Robots usually get the visual systems with a camera for measuring the size of an object and the distance to an object. The visual systems are accurately impossible the size and distance in case of that the locations of the systems is changed and the objects are not on the ground. Thus, in this paper, we developed robot's visual system to measure the size of an object and the distance to an object using two cameras and two-degree robot mechanism. And, we developed the image processing algorism to measure the size of an object and the distance from robot to an object for the visual system, and finally, carried out the characteristics test of the developed visual system. As a result, it is thought that the developed system could accurately measure the size of an object and the distance to an object.