• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.903-914
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• 2020

In this paper, we present a novel algorithm to generate a 3D model of patient-specific orbital implant, which is finally produced by the 3D printer. Given CT (computed tomography) scan data of the defective orbital wall or floor, we compose the depth image of the defect site by using the depth buffering, which is a computer graphics technology. From the depth image, we compute the 3D surface which fills the broken part by interpolating the points around the broken part. By thickening the 3D surface, we get the 3D volume mesh of the orbital implant. Our algorithm generates the patient-specific orbital implant whose shape is accurately coincident to the broken part of the orbit. It provides the significant time efficiency for manufacturing the implant with supporting high user convenience.

• Journal of Sensor Science and Technology
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• v.19 no.2
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• pp.124-129
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• 2010

For the industrial printing applications, the stability of the piezo-driven inkjet printhead is a major requirement. In this paper, we focused on the failure modes of the inkjet printhead and realized a method to detect and repair them at high speed. The printhead monitoring is performed by detecting the residual vibration of the actuating plate using the self- sensing capability of the piezoelectric material. To measure the channel acoustics and to identify the malfunctioning nozzle, we devised the bridge sensing circuitry and failure detection algorithm. The residual vibration signals can be affected by the boundary conditions of the channel acoustics, so it is possible to identify the failure causes by analyzing the monitoring signals. Therefore it is also possible to apply a proper restoring process to the defective printhead. The experimental results show that this method is effective in improving the reliability of the industrial printing.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.6
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• pp.407-414
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• 2023

In this study, an automated jack-up system, applicable to various fields, was employed for 3D concrete printing and developed as a simultaneous liftable 3D concrete printing system. This developed printing system enables safe and precise jack-up by monitoring the measured jack-up distance using Pearson correlation coefficient analysis and a hydraulic system with interquartile range analysis in real-time during 3D concrete printing operations. It is possible to secure the quality of 3D concrete printing structures, which is essential for expanding the application of 3D concrete printing to construct larger structures. Specimens were printed using both conventional 3D concrete printing and simultaneous liftable 3D concrete printing to evaluate the system performance. The printed specimens were investigated using a 3D scanner. The layer-wise diameter and angle of intersection of the scanned specimens were measured, and an analysis was performed to verify the advantages of the simultaneous liftable 3D concrete printing.

• KIPS Transactions on Software and Data Engineering
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• v.9 no.1
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• pp.11-16
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• 2020

3D printing is one of the emerging technologies and getting a lot of attention. To do 3D printing, 3D model is first generated, and then converted to G-code which is 3D printer's operations. Facet, which is a small triangle, represents a small surface of 3D model. Depending on the height or precision of the 3D model, the number of facets becomes very large and so the conversion time from 3D model to G-code takes longer. Apach Hadoop is a software framework to support distributed processing for large data set and its application range gets widening. In this paper, Hadoop is used to do the conversion works time-efficient way. 2-phase distributed algorithm is developed first. In the algorithm, all facets are sorted according to its lowest Z-value, divided into N parts, and converted on several nodes independently. The algorithm is implemented in four steps; preprocessing - Map - Shuffling - Reduce of Hadoop. Finally, to show the performance evaluation, Hadoop systems are set up and converts testing 3D model while changing the height or precision.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.6
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• pp.583-588
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• 2015

Flexible tactile sensors can provide valuable feedback to intelligent robots regarding the environment around them. This is especially important when robots such as, service robots share a workspace with humans. This paper presents a contact force measurement algorithm of a flexible tactile sensor. This sensor is manufactured by a direct-writing technique, which is one 3D printing method, using multi-walled carbon nano-tubes. An analog signal processing circuit has been designed and implemented to reduce noise contained in the sensor output. In addition, a digital version of the Butterworth filter was implemented by software running on a microcontroller. Through various experiments, characteristics of the sensor system have been identified. Based on three traits, an algorithm to detect the contact and measure the contact force has been developed. The entire system showed a promising prospect to detect the contact over a large and curved area.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2164-2169
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• 2005

SFFS(Solid Freeform Fabrication System) can quickly makes models and prototype parts from 3D computer-aided design (CAD) data. Three dimensional printing(3DP) is a kind of the solid freeform fabrication. The 3DP process slices the modeling data into the 50-200um along to z axis. And we pile the powder and make the manufactures. A manufacture is made by the SFFS has the precision of the 50um. Therefore the x-y table of SFFS to move a printhead must be the system that has a high speed and accuracy. So we proposed the SMCSPO algorithm for SFFS. The major contribution is the design of a robust observer for estimating the state and the perturbation of the timing belt system, which is combined with a robust controller. The control performance of the proposed algorithm is compared with PD control by the simulation and the experiment. The control algorithm of the SFFS is presented in the office environment. The system between control system and printhead for the SFFS is also integrated

• Journal of the Korea Computer Graphics Society
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• v.21 no.3
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• pp.11-16
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• 2015

We present a system for generating 3D personalized figures. This system provides 3D figures model modification and combination functions based on the content-awareness. The integrity of the 3D model must be guaranteed at the time of slicing of the 3D model for 3D printing. In addition to this, with 3D printing, we generally have to print a hollow model in order to save money, time, and the integrity of the print. This paper proposes the automatic algorithm that creates the 3D individual figures with depth sensor and the easy UI functions for deformation, thickness adjustment, and combination of the generated 3D figures model based on the content-awareness. Our proposed method maintains the unique features of the generated 3D figures and ensures the successful 3D printing.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1997.06a
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• pp.61-66
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• 1997

For constructing an intelligent multimedia database system for medical diagnosis, we are focusing on two technological points. One is a retrieval algorithm of databases, and the other is a coding algorithm of multimedia contents. For the first, previously we proposed a front-end database preprocessor called“keyword-network”, and in this paper we present its extended model providing an intelligent logical AND searching function especially for medical differential diagnosis. For the second, we present examples of multimedia intellectual coding methods for cardiovascular examination records.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.2
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• pp.48-55
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• 2022

The color image of the brand comes first and is an important visual element that leads consumers to the consumption of the product. To express more effectively what the brand wants to convey through design, the printing market is striving to print accurate colors that match the intention. In 'offset printing' mainly used in printing, colors are often printed in CMYK (Cyan, Magenta, Yellow, Key) colors. However, it is possible to print more accurate colors by making ink of the desired color instead of dotting CMYK colors. The resulting ink is called 'spot color' ink. Spot color ink is manufactured by repeating the process of mixing the existing inks. In this repetition of trial and error, the manufacturing cost of ink increases, resulting in economic loss, and environmental pollution is caused by wasted inks. In this study, a deep learning algorithm to predict printed spot colors was designed to solve this problem. The algorithm uses a single DNN (Deep Neural Network) model to predict printed spot colors based on the information of the paper and the proportions of inks to mix. More than 8,000 spot color ink data were used for learning, and all color was quantified by dividing the visible light wavelength range into 31 sections and the reflectance for each section. The proposed algorithm predicted more than 80% of spot color inks as very similar colors. The average value of the calculated difference between the actual color and the predicted color through 'Delta E' provided by CIE is 5.29. It is known that when Delta E is less than 10, it is difficult to distinguish the difference in printed color with the naked eye. The algorithm of this study has a more accurate prediction ability than previous studies, and it can be added flexibly even when new inks are added. This can be usefully used in real industrial sites, and it will reduce the attempts of the operator by checking the color of ink in a virtual environment. This will reduce the manufacturing cost of spot color inks and lead to improved working conditions for workers. In addition, it is expected to contribute to solving the environmental pollution problem by reducing unnecessarily wasted ink.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.3
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• pp.1-9
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• 2015

In this paper, we implemented the computer vision platform design with MEAN Stack through Raspberry PI 2 model which is an open source platform. we experimented the face recognition, temperature and humidity sensor data logging with WiFi communication under Raspberry Pi 2 model. Especially we directly made the shape of platform with 3D printing design. In this paper, we used the face recognition algorithm with OpenCV software through haarcascade feature extraction machine learning algorithm, and extended the functionality of wireless communication function ability with Bluetooth technology for the purpose of making Android Mobile devices interface. And therefore we implemented the functions of the vision platform for identifying the face recognition characteristics of scanning with PI camera with gathering the temperature and humidity sensor data under IoT environment. and made the vision platform with 3D printing technology. Especially we used MongoDB for developing the performance of vision platform because the MongoDB is more akin to working with objects in a programming language than what we know of as a database. Afterwards, we would enhance the performance of vision platform for clouding functionalities.