• International Journal of Highway Engineering
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• v.15 no.5
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• pp.177-185
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• 2013

PURPOSES : This study attempts to design and establish the road surface condition detection system by using the image processing that is expected to help implement the low-cost and high-efficiency road information detection system by examining technology trends in the field of road surface condition information detection and related case studies. METHODS : Adapted visual information collecting method(setting a stereo camera outside of the vehicle) and visual information algorithm(transform a Wavelet Transform, using the K-means clustering) Experiments and Analysis on Real-road, just as four states(Dry, Wet, Snow, Ice). RESULTS : Test results showed that detection rate of 95% or more was found under the wet road surface, and the detection rate of 85% or more in snowy road surface. However, the low detection rate of 30% was found under the icy road surface. CONCLUSIONS : As a method to improve the detection rate of the mobile road surface condition information detection system developed in this study, more accurate phase analysis in the image processing process was needed. If periodic synchronization through automatic settings of the camera according to weather or ambient light was not made at the time of image acquisition, a significant change in the values of polarization coefficients occurs.

• Journal of the Korean Society of Safety
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• v.37 no.3
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• pp.16-23
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• 2022

This study aims to provide a fundamental material for identifying fire and no-fire signals using the detection signal characteristics of IoT-based fire-detection systems. Unlike analog automatic fire-detection equipment, IoT-based fire-detection systems employ wireless digital communication and are connected to a server. If a detection signal exceeds a threshold value, the measured values are saved to a server within seconds. This study was conducted with the detection data saved from seven fire accidents that took place in traditional markets from 2020 to 2021, in addition to 233 fire alarm data that have been saved in the K institute from 2016 to 2020. The saved values demonstrated variable and continuous VC-Signals. Additionally, we discovered that the detection signals of two fire accidents in the K institution had a VC-Signal. In the 233 fire alarms that took place over the span of 5 years, 31% of smoke alarms and 30% of temperature alarms demonstrated a VC-Signal. Therefore, if we selectively recognize VC-Signals as fire signals, we can reduce about 70% of false alarms.

• Journal of Information Processing Systems
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• v.2 no.3 s.4
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• pp.189-193
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• 2006

In this study we propose an automatic reading system for diagnostic DNA chips. We define a general specification for an automatic reading system and propose a possible implementation method. The proposed system performs the whole reading process automatically without any user intervention, covering image acquisition, image analysis, and report generation. We applied the system for the automatic report generation of a commercialized DNA chip for cervical cancer detection. The fluorescence image of the hybridization result was acquired with a $GenePix^{TM}$ scanner using its library running in HTML pages. The processing of the acquired image and the report generation were executed by a component object module programmed with Microsoft Visual C++ 6.0. To generate the report document, we made an HWP 2002 document template with marker strings that were supposed to be searched and replaced with the corresponding information such as patient information and diagnosis results. The proposed system generates the report document by reading the template and changing the marker strings with the resultant contents. The system is expected to facilitate the usage of a diagnostic DNA chip for mass screening by the automation of a conventional manual reading process, shortening its processing time, and quantifying the reading criteria.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3376-3382
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• 2014

The system developed inspects automatically defects existing on an inner surface of anodically treated aluminum cylinder-tubes. This system consists of automatic inspection software, and electronic endoscope and a conveyor moving device. By applying the optimal brightness conditions to searching for various defects on the inner surface of cylinder tube, the recognition rate of major defects, such as scratch, oxide and weld line reached 99%. If the present visual inspection process is replaced with the automatic defects inspection system, the physical fatigue of the operator could be reduced and the productivity could be increased. The automatic inspection system developed could also improve the quality of the products.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.6
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• pp.754-758
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• 2017

In this paper, we designed and manufactured an automatic control system to minimize or avoid damage by automatically controlling ship engines in case of fog to allow for safer operation. This automatic power control system uses ATmega128 and an RPM detection circuit to measure RPM changes by artificially generating fog in the fog generator. For this purpose, we have created a complete schematic and applied our source code to an ATmega128 for PWM control using a Hall sensor motor. In future, an experiment and safety evaluation using this automatic power control system with an actual ship will be prepared.

• Journal of Advanced Navigation Technology
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• v.17 no.1
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• pp.115-122
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• 2013

Disease diagnostics based on medical imaging is getting popularity day by day. Presence of the atherosclerosis is one of the causes of narrowing of carotid arteries which may block partially or fully blood flow into the brain. Serious brain strokes may occur due to such types of blockages in blood flow. Early detection of the plaque and taking precautionary steps in this regard may prevent from such type of serious strokes. In this paper, we present an automatic image segmentation technique for carotid artery ultrasound images based on active contour approach. In our experimental study, we assume that ultrasound images are properly aligned before applying automatic image segmentation. We have successfully applied the automatic segmentation of carotid artery ultrasound images using snake based model. Qualitative comparison of the proposed approach has been made with the manual initialization of snakes for carotid artery image segmentation. Our proposed approach successfully segments the carotid artery images in an automated way to help radiologists to detect plaque easily. Obtained results show the effectiveness of the proposed approach.

• The Journal of the Korea Contents Association
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• v.20 no.5
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• pp.609-622
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• 2020

With the development of society, the scale of the statute is not only increasing, but also the content is getting complicated. The scale of safety standards existing in the law is also increasing and specialized, making it difficult to integrate and manage to minimize conflicts or overlaps among safety standards. For the integrated management of safety standards, a technology that searches for and extracts safety standards in laws and regulations must first be secured. In this study, considering the limitations of time and manpower, a tool for automatic detection of safety standards is developed based on several specific cases. The safety standards classified in the previous studies and the safety standards announced by the Ministry of Interior and Safety were analyzed, and also statute information which includes safety standards extracted by the National Disaster Management Institute in 2018 was collected. After the collected laws were refined and morphological analysis was performed, a safety standard thesaurus was constructed and indexed to develop a safety standard search tool. When automatic search tools are routinely applied to find safety standards in the future, it is expected that these tools will help to solve overlapping or conflicting problems of complex safety standards.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.31-37
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• 2009

This paper presents an efficient frame synchronization strategy with the identification of modulation type for Digital Video Broadcasting-Satellite second generation (DVB-S2). To detect the Start Of Frame (SOF) and identify a modulation mode at low SNR, we propose a new correlator structure and a low complexity Automatic Gain Controller (AGC). The proposed frame synchronization architecture can reduce about 93% multipliers and 89% adders compared with the direct implementation of the Differential - Generalized Post Detection Integration (D-GPDI) algorithm which is very complex and the proposed a low complexity AGC consists of only 5 multipliers and 3 adders. The proposed architecture has been thoroughly verified on the Xilinx Virtex II FPGA board.

• Journal of Veterinary Clinics
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• v.19 no.1
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• pp.37-42
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• 2002

To develop an automatic detecting system of body temperature of dairy cattle while milking, measurement of the temperature of mammary skin using three thermometers attached into the lining of teat cup was carried out for 23 dairy cattle, whereas measurement of the temperature of milk while milking was also performed for 263 animals. For the latter experiment, three thermometers were attached at 10cm(left and right) and 20 cm away from an individual milk collector on the milk transporting hose. Taking the rectal temperature was accompanied all the time for the experiments. The measurement of the temperature of mammary skin using teat cup was successful for 11 of 23 dairy cattle(47.8%) and the mean temperature was $33.5^{\circ}C$ with the mean difference of $5.2^{\circ}C$ from the mean rectal temperature. The measurement of the temperature of milk using the thermometers onto the milk transporting hose while milking was very successful , From 37.3 to $38.4^{\circ}C$ of rectal temperature, the temperature of milk was almost the same and from 38.5 to $39.5^{\circ}C$ of rectal temperature, the temperature of milk tended to be low with the difference of 0.1$^{\circ}C$. From 39.6 to $41^{\circ}C$ of rectal temperature, the temperature of milk tended to be low with the difference of $0.2-0.6^{\circ}C$. These results indicated that automatic detection of body temperature whether low or high can be possible if the temperature of milk is taken while milking and if it is connected to the integration system by on-line.

• International Journal of Computer Science & Network Security
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• v.23 no.12
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• pp.151-160
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• 2023

Breast cancer is the most dangerous and deadly form of cancer. Initial detection of breast cancer can significantly improve treatment effectiveness. The second most common cancer among Indian women in rural areas. Early detection of symptoms and signs is the most important technique to effectively treat breast cancer, as it enhances the odds of receiving an earlier, more specialist care. As a result, it has the possible to significantly improve survival odds by delaying or entirely eliminating cancer. Mammography is a high-resolution radiography technique that is an important factor in avoiding and diagnosing cancer at an early stage. Automatic segmentation of the breast part using Mammography pictures can help reduce the area available for cancer search while also saving time and effort compared to manual segmentation. Autoencoder-like convolutional and deconvolutional neural networks (CN-DCNN) were utilised in previous studies to automatically segment the breast area in Mammography pictures. We present Automatic SegmenAN, a unique end-to-end adversarial neural network for the job of medical image segmentation, in this paper. Because image segmentation necessitates extensive, pixel-level labelling, a standard GAN's discriminator's single scalar real/fake output may be inefficient in providing steady and appropriate gradient feedback to the networks. Instead of utilising a fully convolutional neural network as the segmentor, we suggested a new adversarial critic network with a multi-scale L1 loss function to force the critic and segmentor to learn both global and local attributes that collect long- and short-range spatial relations among pixels. We demonstrate that an Automatic SegmenAN perspective is more up to date and reliable for segmentation tasks than the state-of-the-art U-net segmentation technique.