• Macromolecular Research
• /
• v.17 no.2
• /
• pp.110-115
• /
• 2009

The electrical, morphological and rheological properties of melt and dry mixed composites of poly ethylene (PE)/graphite (Gr), polypropylene (PP)/Gr and PP/nickel-coated carbon fiber (NCCF) were investigated as a function of filler type, filler content and processing temperature. The electrical conductivities of dry mixed PP/NCCF composites were increased with decreasing processing temperature. For the melt mixed PP/NCCF composites, the electrical conductivities were higher than those of the melt mixed PE/Gr and PP/Gr composites, which was attributed to the effect of the higher NCCF aspect ratio in allowing the composites to form a more conductive network in the polymer matrix than the graphite does. From the results of morphological studies, the fillers in the dry mixed PP/NCCF composites were more randomly dispersed compared to those in the melt mixed PP/NCCF composites. The increased electrical conductivities of the dry mixed composites were attributed to the more random dispersion of NCCF compared to that of the melt mixed PP/NCCF composites. The complex viscosities of the PP/Gr composites were higher than those of the PP/NCCF composites, which was attributed to the larger diameter of the graphite particles than that of the NCCF. Furthermore, the fiber orientation in the 'along the flow' direction during melt mixing was attributed to the decreased complex viscosities of the melt mixed PP/NCCF composites compared those of the melt mixed PP/Gr composites.

• Journal of Biosystems Engineering
• /
• v.38 no.1
• /
• pp.55-63
• /
• 2013

Purpose: The present study aimed at image processing methods for automatic cell pattern recognition and morphological analysis for tissue engineering applications. The primary aim was to ascertain the novel algorithm of adaptive brightness correction from microscopic images for use as a potential image analysis. Methods: General microscopic image of cells has a minor problem which the central area is brighter than edge-area because of the light source. This may affect serious problems to threshold process for cell-number counting or cell pattern recognition. In order to compensate the problem, we processed to find the central point of brightness and give less weight-value as the distance to centroid. Results: The results presented that microscopic images through the brightness correction were performed clearer than those without brightness compensation. And the classification of mixed cells was performed as well, which is expected to be completed with pattern recognition later. Beside each detection ratio of hBMSCs and HeLa cells was 95% and 92%, respectively. Conclusions: Using this novel algorithm of adaptive brightness correction could control the easier approach to cell pattern recognition and counting cell numbers.

• Design & Manufacturing
• /
• v.17 no.2
• /
• pp.55-61
• /
• 2023

With femtosecond (fs) laser pulse irradiation on metals, various types of nano- and micro-scale structures can be naturally induced at the surface through laser-matter interaction. Two notable structures are laser-induced periodic surface structures (LIPSSs) and cone/spike structures, which are known to significantly modify the optical and physical properties of metal surfaces. In this work, we irradiate fs laser pulses onto various types of metals, cold-rolled steel, pickled & oiled steel, Fe-18Cr-8Ni alloy, Zn-Mg-Al alloy coated steel, and pure Cu which can be useful for precise molding and imprinting processes, and adjust the morphological profiles of LIPSSs and cone/spike structures for clear structural coloration and a larger range of surface wettability control, respectively, by changing the fluence of laser and the speed of raster scan. The periods of LIPSSs on metals used in our experiments are nearly independent of laser fluence. Accordingly, the structural coloration of the surface with LIPSSs can be optimized with the morphological profile of LIPSSs, controlled only by the speed of the raster scan once the laser fluence is determined for each metal sample. However, different from LIPSSs, we demonstrate that the morphological profiles of the cone/spike structures, including their size, shape, and density, can be manipulated with both the laser fluence and the raster scan speed to increase a change in the contact angle. By injection molding and imprinting processes, it is expected that fs laser-induced surface structures on metals can be replicated to the plastic surfaces and potentially beneficial to control the optical and wetting properties of the surface of injection molded and imprinted products.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2002.10a
• /
• pp.646-649
• /
• 2002

It can be effect on diagnosis of hydraulic machining system to analyze working conditions with shape characteristics of wear debris in a lubricated machine. But, in order to predict and estimate working conditions, it is need to analyze the shape characteristics of wear debris and to identify. Therefor, if shape characteristics of wear debris is identified by computer image analysis and the neural network, it is possible to find the cause and effect of moving condition. In this study, wear debris in the lubricant oil are extracted by membrane filter, and the quantitative value of shape characteristics of wear debris we calculated by the digital image processing. This morphological informations are studied and identified by the artificial neural network. The purpose of this study is In apply morphological characteristics of wear debris to prediction and estimation of working condition in hydraulic driving systems.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.9 no.6
• /
• pp.345-351
• /
• 2014

This paper presents pedestrian recognition to improve performance for vehicle safety system or surveillance system. Pedestrian detection method using HOG (Histograms of Oriented Gradients) has showed 90% recognition rate. But if someone takes a picture in the rain, the image may be distorted by rain streaks and recognition rate goes down by 62%. To solve this problem, we applied image decomposition method using MCA (Morphological Component Analysis). In this case, rain removal method improves recognition rate from 62% to 70%. However, it is difficult to apply conventional image decomposition method using MCA on vehicle safety system or surveillance system as conventional method is too slow for real-time system. To alleviate this issue, we propose a rain removal method by using low-pass filter and DCT (Discrete Cosine Transform). The DCT helps separate the image into rain components. The image is removed rain components by Butterworth filtering. Experimental results show that our method achieved 90% of recognition rate. In addition, the proposed method had accelerated processing time to 17.8ms which is acceptable for real-time system.

• Proceedings of the Korea Contents Association Conference
• /
• 2009.05a
• /
• pp.23-29
• /
• 2009

Blob detection is an essential ingredient process in some computer applications such as intelligent visual surveillance. However, previous blob detection algorithms are still computationally heavy so that supporting real-time multi-channel intelligent visual surveillance in a workstation or even one-channel real-time visual surveillance in a embedded system using them turns out prohibitively difficult. In this paper, we propose a fast and precise blob detection algorithm for visual surveillance. Blob detection in visual surveillance goes through several processing steps: foreground mask extraction, foreground mask correction, and connected component labeling. Foreground mask correction necessary for a precise detection is usually accomplished using morphological operations like opening and closing. Morphological operations are computationally expensive and moreover, they are difficult to run in parallel with connected component labeling routine since they need much different processing from what connected component labeling does. In this paper, we first develop a fast and precise foreground mask correction method utilizing on neighbor pixel checking which is also employed in connected component labeling so that the developed foreground mask correction method can be incorporated into connected component labeling routine. Through experiments, it is verified that our proposed blob detection algorithm based on the foreground mask correction method developed in this paper shows better processing speed and more precise blob detection.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.21 no.3
• /
• pp.576-586
• /
• 1996

Original binary image can be reconstructed by morphological bymorphological skeleton(MS) image. And then, the information of MS image points can be applied to a pattern recognition andimage communication. But if we apply MS to a pattern recognition and image communication, there are two problems. That is to say, binary MS processing times is long and skeleton points of MS are high redundancy. And then, to solve these problems, this paper proposes DGMS. After simulating by the proposed method to $256{\times}256$ binary image which is GIRL, we reduce processing time and skeleton points about 1.5~6.5% comparing with the result of GMS method.

• Journal of the Semiconductor & Display Technology
• /
• v.21 no.4
• /
• pp.92-98
• /
• 2022

This paper proposes a new method of the traffic signal detection and the recognition in an HSI color model. The proposed method firstly converts a ROI image in the RGB model to in the HSI model to segment the color of a traffic signal. Secondly, the segmented colors are dilated by the morphological processing to connect the traffic signal light and the signal light case and finally, it extracts the traffic signal light and the case by the aspect ratio using the connected component analysis. The extracted components show the detection and the recognition of the traffic signal lights. The proposed method is implemented using C language in Raspberry Pi 4 system with a camera module for a real-time image processing. The system was fixedly installed in a moving vehicle, and it recorded a video like a vehicle black box. Each frame of the recorded video was extracted, and then the proposed method was tested. The results show that the proposed method is successful for the detection and the recognition of traffic signals.

• The Korean Journal of Applied Statistics
• /
• v.22 no.3
• /
• pp.569-584
• /
• 2009

Edge detection in images has been widely used in image processing system and computer vision. Morphological edge detection has used structuring elements with fixed shapes. This paper presents morphological operators with non-fixed shape kernels, or amoebas, which take into account the image contour variations to adapt their shape. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with PFOM and ROC curves. The Experiments demonstrate that these novel operators outperform classical morphological operations with a fixed, space-invariant structuring elements for edge detection applications.

• Proceedings of the KSPS conference
• /
• 2002.11a
• /
• pp.101-104
• /
• 2002

The purpose of this study was to investigate which model among Fullist, Decomposition, and Hybrid was appropriate for explaining the process of Korean verb, especially on tense prefinal ending, connective ending, and morphological passive affix. Three experiment was performed. The results of experiment 1, 2, 3 suggest that it is necessary for a new model of Korean verb processing.