• Journal of Environmental Health Sciences
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• v.39 no.6
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• pp.522-531
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• 2013

Objectives: A field survey was conducted in a hog-raising industry in order to help develop personal protective equipment for workers which would secure the safety and the health of these workers. The attempt by this study will help enhance safety in the livestock industry and contribute to the advancement of the industry. Method: The study first selected a total of 111 workers from the hog-raising industry as research participants and designed a survey with questions on general characteristics, indoor and outdoor working environments, how the workers would in practice wear or purchase the working clothes, what needs to be improved in these new working clothes, how much the workers would be likely to accept the working clothes and protective equipment, and lastly, conditions of the communicable disease control overgarment. The collected data underwent frequency analysis and cross analysis with SPSS 21.0. Result: The research targets' average age was 50 years. Work efficiency by environmental factor was normal, but all age groups had experience of accidents (79.3%). Major wounded parts were under elbow and under knee. Protective equipment most commonly worn was helmet (83.4%), gloves (98.2%) and boots (99.1%), and satisfaction with them was normal at 3.41. Working clothing most commonly worn was old clothing (31.8%) and everyday wear (17.6%) and satisfaction with it was low. Considering the improvement of working clothing, they required attached pouches, elasticity and deodorization. The acceptability of improved working clothing was high at 69.2%. Conclusion: After problems have been addressed in relevant future research, what has been learned from the concerned study will be referred to as a useful basic reference when the relevant field works to develop high-quality working clothing and protective equipment for workers in the hog-raising industry.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.551-557
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• 2013

In intelligent robot research, hand gesture recognition has been an important issue. And techniques that recognize simple gestures are commercialized in smart phone, smart TV for swiping screen or volume control. For gesture recognition, robust hand detection is important and necessary but it is challenging because hand shape is complex and hard to be detected in cluttered background, variant illumination. In this paper, we propose efficient hand detection algorithm for detecting pointing hand for recognition of place where user pointed. To minimize false detections, ROIs are generated within the compact search region using skin color detection result. The ROIs are verified by HOG-SVM and pointing direction is computed by both detection results of head-shoulder and hand. In experiment, it is shown that proposed method shows good performance for hand detection.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.6
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• pp.621-628
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• 2015

This paper describes an algorithm for detecting vehicles detection in real time. The proposed algorithm has the technique based on computer vision and image processing. In real, complex environment such as one with road traffic, many algorithms have great difficulty such as low detection rate and increasing computational time due to complex backgrounds and rapid changes. To overcome this problem in this paper, the proposed algorithm consists of the following methods. First, to effectively separate the candidate regions, we use vertical and horizontal edge information, and shadow values from input image sequences. Second, we extracts features by using HOG from the selected candidate regions. Finally, this paper uses the OS fuzzy-ELM based on SLFN to classify the extracted features. The experimental results show that the proposed method perform well for detecting vehicles and improves the accuracy and the computational time of detecting.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.465-469
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• 2017

In this paper we propose a human body tracking method for application of smartphones. The conventional human body tracking method is divided into a sensor-based method and a vision-based method. The sensor-based methods have a weakness in that tracking accuracy is low due to cumulative error of position information. The vision-based method has no cumulative error, but it requires reduction of the computational complexity for application of smartphone. In this paper we use the improved HOG algorithm as a human body tracking method for application of smartphone. The improved HOG algorithm is implemented through downsampling and frame sampling. Gaussian pyramid is applied for downsampling, and uniform sampling is applied for frame sampling. We measured the proposed algorithm on two devices, four resolutions, and four frame sampling intervals. We derive the best detection rate among downsampling and frame sampling parameters that can be applied in realtime.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.7
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• pp.996-1003
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• 2022

In this paper, we present a new method for determining the scan line and range for vision-based 1-D barcode recognition. This is a study on how to detect valid barcode representative points and directions by applying the DBSCAN clustering method based on block HOG (histogram of gradient) and determine scan lines and barcode crosslines based on this. In this paper, the minimum and maximum search techniques were applied to determine the cross-line range of barcodes based on the obtained scan lines. This can be applied regardless of the barcode size. This technique enables barcode recognition even by detecting only a partial area of the barcode, and does not require rotation to read the code after detecting the barcode area. In addition, it is possible to detect barcodes of various sizes. Various experimental results are presented to evaluate the performance of the proposed technique in this paper.

• Journal of Korea Multimedia Society
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• v.20 no.8
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• pp.1187-1199
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• 2017

In recent years, research about Natural User Interface (NUI) has become focused because NUI system can give natural feelings for users in virtual reality. Most important thing in NUI system is how to communicate with the computer system. There are many things to interact with users such as speech, hand gestures, body actions. Among them, hand gesture is suitable for the purpose of NUI because people often use a relatively high frequency in daily life and hand gesture have meaning only by itself. This hand gestures called multi-cultural hand gesture and we proposed the method to recognize this kind of hand gestures. Proposed method is composed of Histogram of Oriented Gradients (HOG) used for hand shape recognition and Histogram of Oriented Displacements (HOD) used for hand center point trajectory recognition.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.06a
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• pp.306-308
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• 2016

신호등 검출은 지능형 교통 시스템에서 매우 중요하며 최근 신호등 검출 관련한 연구가 활발히 진행 중이다. 하지만 기존의 신호등검출 알고리듬의 문제점은 조명의 변화에 민감하다는 문제점이 있다. 이러한 문제점을 해결하기 위하여 본 논문에서는 다음과 같은 신호등 검출 알고리듬을 제안한다. 먼저 제안하는 색상지도와 HSV(Hue-Saturation-Value)를 이용하여 신호등의 후보를 검출한다. 검출한 신호등의 후보로부터 HOG(Histogram of Oriented Gradient) 서술자를 이용하여 특징을 추출한 다음 최종적으로 선형 SVM(Support Vector Machine)을 이용하여 신호등을 검출하는 알고리듬을 제안한다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3971-3975
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• 2013

This paper introduces an Augmented Reality system recognizing hand gestures and shows results of the evaluation. The system's user can interact with artificial objects and manipulate their position and motions simply by his hand gestures. Hand gesture recognition is based on Histograms of Oriented Gradients (HOG). Salient features of human hand appearance are detected by HOG blocks. Blocks of different sizes are tested to define the most suitable configuration. To select the most informative blocks for classification multiclass AdaBoostSVM algorithm is applied. Evaluated recognition rate of the algorithm is 94.0%.

• Journal of Multimedia Information System
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• v.4 no.1
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• pp.33-38
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• 2017

This article suggests a new algorithm for detecting two-wheelers on the road that have various shapes according to viewpoints. Because of complicated shapes, it is more difficult than detecting a human. In general, the Histograms of Oriented Gradients(HOG) feature is well known as a useful method of detecting a standing human. We propose a method of detecting a human on a two-wheelers using the spatial relocation of HOG (Histogram of Oriented Gradients) features. And this paper adapted the contrast method which is generally using in the image process to improve the detection rate. Our experimental results show that a two-wheelers detection system based on proposed approach leads to higher detection accuracy, less computation, and similar detection time than traditional features.

• Korean Journal of Veterinary Research
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• v.6 no.1
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• pp.31-36
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• 1966

The free amino acid contents in several tissues of swine were analyzed qualitatively by means of two dimentional paper chromatography. The tissues used were liver, kidney and spleen that were obtained from normal, immunized and hog cholera infected swines. The results obtained are as follows: 1. Liver: 20 amino acids were detected in normal, 17 in immunized and 15 in infected swines. 2. Kidney: 16 amino acids were detected in normal, 13 in immunized and infected swines. 3. Spleen: 15 amino acids were detected in normal in immunized and 13 in infected swines. 4. Glutamic acid, leucine, serine and threonine were present in high concentration in all of the cases examined. 5. The free amino acids were appeard to be decreased in the infected tissues with hog cholera virus.