• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.65-72
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• 2006

The traffic lights detection and recognition system is an essential module of the driver warning and assistance system. A method which is a color vision-based real time detection and recognition of traffic lights is presented in this paper This method has four main modules : traffic signals lights detection module, traffic lights boundary candidate determination module, boundary detection module and recognition module. In traffic signals lights detection module and boundary detection module, the color thresholding and the subtraction value of saturation and intensity in HSI color space and detection probability mask for lights detection are used to segment the image. In traffic lights boundary candidate determination module, the detection mask of traffic lights boundary is proposed. For the recognition module, the AND operator is applied to the results of two detection modules. The input data for this method is the color image sequence taken from a moving vehicle by a color video camera. The recorded image data was transformed by zooming function of the camera. And traffic lights detection and recognition experimental results was presented in this zoomed image sequence.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.2
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• pp.255-263
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• 2016

Lane Keeping Assistance System (LKAS) is a kind of Advanced Driver Assistance Systems (ADAS) which are developed to automate/ adapt/ enhance vehicle systems for safety and better driving. The main system function of LKAS is to support the driver in keeping the vehicle within the current lane. LKAS acquires information on the position of the vehicle within the lane and, when required, sends commands to actuators to influence the lateral movement of the vehicle. Recently, the vehicles equipped with LKAS are commercially available in a few vehicle-advanced countries and the installation of LKAS increases for safety enhancement. The test procedures for LKAS evaluations are being discussed and developed in the international committees such as ISO (the International Organization for Standardization) and UNECE (United Nations Economic Commission for Europe). In Korea, the evaluations of LKAS for vehicle safety are planned to be introduced in 2016 KNCAP (Korean New Car Assessment Program). Therefore, the test procedures of LKAS suitable for domestic road and traffic conditions, which accommodate international standards, should be developed. In this paper, some bullet points of the test procedures for LKAS are discussed and proposed by extensive researches of previous documents and reports, which are released in public in regard to lateral test procedures including LKAS and Lane Departure Warning System (LDWS). And then, to evaluate the validity of the proposed test procedures, a series of experiments were conducted using commercially available two vehicles equipped with LKAS. Later, it can be helpful to make a draft considering domestic traffic situations for test procedures of LKAS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.9
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• pp.1979-1986
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• 2010

Biological early warning system detects toxicity by looking at behavior of organisms in water. The system uses classifier for judgement about existence and amount of toxicity in water. Boosting algorithm is one of possible application method for improving performance in a classifier. Boosting repetitively change training example set by focusing on difficult examples in basic classifier. As a result, prediction performance is improved for the events which are difficult to classify, but the information contained in the events which can be easily classified are discarded. In this paper, an incremental learning method to overcome this shortcoming is proposed by using the extended data expression. In this algorithm, decision tree classifier define class distribution information using the weight parameter in the extended data expression by exploiting the necessary information not only from the well classified, but also from the weakly classified events. Experimental results show that the new algorithm outperforms the former Learn++ method without using the weight parameter.

• Transactions of the Korean Society of Automotive Engineers
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• v.24 no.6
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• pp.627-634
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• 2016

In this paper, an augmented video generation method to evaluate the performance of lane departure warning system is proposed. In our system, the input is a video which have road scene with general clean lane, and the content of output video is the same but the lane is synthesized with contamination image. In order to synthesize the contamination lane image, two approaches were used. One is example-based image synthesis, and the other is background-based image synthesis. Example-based image synthesis is generated in the assumption of the situation that contamination is applied to the lane, and background-based image synthesis is for the situation that the lane is erased due to aging. In this paper, a new contamination pattern generation method using Gaussian function is also proposed in order to produce contamination with various shape and size. The contamination lane video can be generated by shifting synthesized image as lane movement amount obtained empirically. Our experiment showed that the similarity between the generated contamination lane image and real lane image is over 90 %. Futhermore, we can verify the reliability of the video generated from the proposed method through the analysis of the change of lane recognition rate. In other words, the recognition rate based on the video generated from the proposed method is very similar to that of the real contamination lane video.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.274-276
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• 2016

Recently due to increase of tobacco users, many problems have been issued. Not only smoking in public places, smoking indoors as well causes harm to non-smoking people. Smoking booths that are installed but the quality is considerably less and purification devices are not correctly installed, which leads to harm the people around the smoking booth. In this paper, we introduce the "Augmented Reality Billboard" in order for smokers to effectively recognize the non-smoking warning image and healthy warning messages, Kinect Camera Sensor and Augmented Reality (AR) functions are used to recognize the motion of a person to coordinate the corresponding coordinate values.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3904-3922
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• 2022

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.292-297
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• 2004

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) which is independent of the CNC vendor. The OAC and machine tools with OAC led the convenient environment where it is possible to implement user-defined application programs efficiently within CNC. Tis paper proposes a method of operational fault cause diagnosis which is based on the status of programmable logic controller (PLC) in machine tools with OAC. The operational fault is defined as a disability state occurring during normal operation of machine tools. The faults are occupied by over 70% of all faults and are also unpredictable as most of them occur without any warning. Two diagnosis models, the switching function (SF) and the step switching function (SSF), are propose in order to diagnose the fault cause quickly and exactly. The cause of an occurring fault is logically diagnosed through a fault diagnosis system (FDS) using the diagnosis models. A suitable interface environment between CNC and develope application modules is constructed in order to implement the diagnostic functions in the CNC domain. The diagnosed results were displayed on a CNC monitor for machine operators and provided to a remote site through a web browser. The result of his research could be a model of the fault cause diagnosis and the remote monitoring for machine tools with OAC.

• Journal of Mechanical Science and Technology
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• v.19 no.8
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• pp.1597-1610
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• 2005

The conventional computerized numerical controller (CNC) of machine tools has been increasingly replaced by a PC-based open architecture CNC (OAC) that is independent of a CNC vendor. The OAC and machine tools with an OAC have led to a convenient environment in which user-defined applications can be efficiently implemented within a CNC. This paper proposes a method of diagnosing the cause of operational faults. The method is based on the status of a programmable logic controller in machine tools with an OAC. An operational fault is defined as a disability that occurs during the normal operation of machine tools. Operational faults constitute more than 70 percent of all faults and are also unpredictable because most of them occur without any warning. To quickly and correctly diagnose the cause of an operational fault, two diagnostic models are proposed: the switching function and the step switching function. The cause of the fault is logically diagnosed through a fault diagnosis system using diagnostic models. A suitable interface environment between a CNC and developed application modules is constructed to implement the diagnostic functions in the CNC domain. The results of the diagnosis were displayed on a CNC monitor for machine operators and transmitted to a remote site through a Web browser. The proposed diagnostic method and its results were useful to unskilled machine operators and reduced the machine downtime.

• Journal of Auto-vehicle Safety Association
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• v.7 no.3
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• pp.30-34
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• 2015

This study examined the Korean drivers' acceptance of SAS(Speed Assistance systems) and traffic sign conditions in Korea roads for SLIF(Speed Limit Information Function) that is a part of SAS. Exceeding the speed limit is a factor in the severity of many road accidents and SAS would help the driver to observe a speed limit by warning and/or effectively limiting the speed of the vehicle. SAS are in the initial phase in Korea, Korean drivers could not be familiar with automatical speed limiting during driving, SAS interface design would be considered to be more readily acceptable to the public. And advanced SAS have been introduced onto the market which are able to inform the driver of the current speed limit based on camera and/or digital maps based SLIF. These systems are based on external data using sensors, so environmental conditions are an important factor which could cause malfunction of SLIF functions.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.2
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• pp.238-246
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• 2021

Collision of small vessels such as fishing boats cause great personal injury. Prior to this study, the collision prevention algorithm was developed to assess the collision risk and make the collision alarm. However, a service provided for safety, such as a collision warning, not only prevents risks, but also requires a certain degree of user satisfaction to function effectively. In this study, the collision prevention algorithm for small vessels was improved to be more practical, and the effects of the improvement were confirmed by applying the algorithm. A survey conducted on the users of the collision warning service confirmed the user requirements for improving the accuracy of the collision warning system and reducing the volume and number of alarms. Accordingly, the algorithm was improved for user satisfaction, and the actual vessel experiment was performed applying the improved algorithm in an actual maritime environment. As a result, the frequency of alarm occurrence decreased compared to former algorithm, but the alarm was relatively steadily generated in dangerous situations. It was analyzed that the accuracy and practicality of the collision alarm were improved. If the practicality and reliability of the improved algorithm are verified in the further study, it will be able to effectively contribute to the prevention of collisions of small vessels.