• Journal of Biomedical Engineering Research
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• 제41권5호
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• pp.195-202
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• 2020

Needle detection in ultrasound images is sometimes difficult due to obstruction of fat tissues. Accurate needle detection using continuous ultrasound (CUS) images is a vital stage of treatment planning for tissue biopsy and brachytherapy. The main goal of the study is classified into two categories. First, new detection model, i.e. D-Attention Unet, is developed by combining the context information of 3D medical data and CUS images. Second, the D-Attention Unet model was compared with other models to verify its usefulness for needle detection in continuous ultrasound images. The continuous needle images taken with ultrasonic waves were converted into still images for dataset to evaluate the performance of the D-Attention Unet. The dataset was used for training and testing. Based on the results, the proposed D-Attention Unet model showed the better performance than other 3 models (Unet, D-Unet and Attention Unet), with Dice Similarity Coefficient (DSC), Recall and Precision at 71.9%, 70.6% and 73.7%, respectively. In conclusion, the D-Attention Unet model provides accurate needle detection for US-guided biopsy or brachytherapy, facilitating the clinical workflow. Especially, this kind of research is enthusiastically being performed on how to add image processing techniques to learning techniques. Thus, the proposed method is applied in this manner, it will be more effective technique than before.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 한국소성가공학회 2002년도 금형가공 심포지엄
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• pp.285-291
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• 2002

The shearing process for the sheet metal is normally used in the precision elements such as a frame of TFT-LCD or lead frame of If chips. In these precision elements, the burr formation prevents the system assembly and needs the additional burr removing process. In this paper, we developed the small size NC punching system which has an aligning kinematics between the rectangular shaped punch and die. The punch is driven by an ai cylinder and the sheet metal is moving on the X-Y table system which is driven by two stewing motors. The microprocessor control the whole system and communicate with the monitoring PC by RS232C serial communication protocol. The graphic user interface program in PC monitors nil control the punching system. The cross shaped joint hinge supports the punching die and positioned by two differential screws, whose are installed in perpendicular directions. The aligning between the punch and die is performed using the sheets of half thickness(0.1mm Brass) of the real process for the frame of the TFT-LCD. Using half thickness Brass, the burr formation is magnified and we can decide the aligning direction more easily then using the real thickness(0.2mm) Aluminum. In this paper, the aligning results are measured manually using the SEM photographs and we hope to make the automated aligning procedures using some kinds of image processing techniques.

• Journal of Sensor Science and Technology
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• 제14권4호
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• pp.272-277
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• 2005

A CMOS active pixel sensor has been designed and fabricated using standard 2-poly and 4-metal $0.35{\mu}m$ CMOS processing technology. The CMOS active pixel sensor has been made up of a unit pixel having a highly sensitive PMOSFET photo-detector and electronic shutters that can control the light exposure time to the PMOSFET photo-detector, correlated-double sampling (CDS) circuits, and an 8-bit two-step flash analog to digital converter (ADC) for digital output. This sensor can obtain a stable photo signal in a wide range of light intensity. It can be realized with a special function of an electronic shutter which controls the light exposure-time in the pixel. Moreover, this sensor had obtained the digital output using an embedded ADC for the system integration. The designed and fabricated image sensor has been implemented as a $128{\times}128$ pixel array. The area of the unit pixel is $7.60{\mu}m{\times}7.85{\mu}m$ and its fill factor is about 35 %.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권10호
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• pp.3955-3971
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• 2020

Due to the significant increase in the use of autonomous car technology, it is essential to integrate this technology with high-precision digital map data containing more precise and accurate roadway information, as compared to existing conventional map resources, to ensure the safety of self-driving operations. While existing map technologies may assist vehicles in identifying their locations via Global Positioning System, it is however difficult to update the environmental changes of roadways in these maps. Roadway vision algorithms can be useful for building autonomous vehicles that can avoid accidents and detect real-time location changes. We incorporate a hybrid architectural design that combines unsupervised classification of vision data with supervised joint fusion classification to achieve a better noise-resistant algorithm. We identify, via a deep learning approach, an intelligent hybrid fusion algorithm for fusing multimodal vision feature data for roadway classifications and characterize its improvement in accuracy over unsupervised identifications using image processing and supervised vision classifiers. We analyzed over 93,000 vision frame data collected from a test vehicle in real roadways. The performance indicators of the proposed hybrid fusion algorithm are successfully evaluated for the generation of roadway digital maps for autonomous vehicles, with a recall of 0.94, precision of 0.96, and accuracy of 0.92.

• Journal of Digital Convergence
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• 제14권11호
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• pp.319-324
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• 2016

In the case of robot and Argument Reality applications using a camera in environments, a technology to estimate planes is a very important technology. A RGB-D camera can get a three-dimensional measurement data even in a flat which has no information of the texture of the plane;, however, there is an enormous amount of computation in order to process the point-cloud data of the image. Furthermore, it could not know the number of planes that are currently observed as an advance, also, there is an additional operation required to estimate a three dimensional plane. In this paper, we proposed the real-time method that decides the number of planes automatically and estimates the three dimensional plane by using the continuous data of an RGB-D camera. As experimental results, the proposed method showed an improvement of approximately 22 times faster speed compared to processing the entire data.

• Korean Journal of Food Science and Technology
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• 제27권4호
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• pp.525-531
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• 1995

Three quality factors of bread during baking process were measured to develop neural network models for bread baking process. Firstly, volume and browning changes during bread baking process were measured using image processing technique and temperature changes inside the bread during process were measured by K-type thermocouples. Relationships among them showed nonlinearity. Secondly, multilayer perception structure with error back propagation learning was used to construct neural network models. Three neural network models for volume, browning, and bread temperature were developed respectively. Developed models showed good performance with predictive error of 4.62% for volume and browning changes after 30 seconds, 7.38% for volume and browning changes after 2 minutes, and 1.09% for temperature change inside the bread respectively.

• The Journal of the Korea institute of electronic communication sciences
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• 제12권2호
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• pp.325-330
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• 2017

Face recognition technology has been studied for decades and is being used in various areas such as security, entertainment, and mobile services. The main problem with face recognition technology is that the recognition rate is significantly reduced depending on the environmental factors such as brightness, illumination angle, and image rotation. Therefore, in this paper, we propose a robust face recognition against lighting variation using CNN which has been recently re-evaluated with the development of computer hardware and algorithms capable of processing a large amount of computation. For performance verification, PCA, LBP, and DCT algorithms were compared with the conventional face recognition algorithms. The recognition was improved by 9.82%, 11.6%, and 4.54%, respectively. Also, the recognition improvement of 5.24% was recorded in the comparison of the face recognition research result using the existing neural network, and the final recognition rate was 99.25%.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• 제8권6호
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• pp.491-496
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• 2015

Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.

• Journal of Korean Tunnelling and Underground Space Association
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• 제16권4호
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• pp.387-402
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• 2014

In congested urban areas, constructions of tunnel structures have became necessary due to a lack of surface space. The excavation of any tunnel generated the ground disturbances of surrounding ground and displacements is major concern. Therefore, a study of tunnel stability is necessary. In this study, the authors have investigated the stability and failure pattern of tunnel through the model tunnel test. In this study, the close range photogrammetry was used to measure the ground deformation. The measured data was converted to displacement vectors and contours. And then it compared to FE analysis and empirical formula. In addition, this study presented the comparison between steel pipe reinforced model tunnel and unreinforced model tunnel. The ground deformation for both the steel pipe reinforced model tunnel and the unreinforced model tunnel was analysed.

• Archives of design research
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• 제19권2호
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• pp.273-282
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• 2006

The earlier animations aimed to express the characters realistically by making the illustrations look like moving and alive. Since then, animations have been influenced by development of media technology, men's changed mentality and evolvement of diverse social phenomena, while influencing them, too. Among them, the computer which emerged first in 1946 has sewed to more diversify the tools for realistic expressions of animations, and further, enhance the intellectual power of expression media only to expand the new visual expressions and thereby, usher in a multi-media video information environment. Moreover, this technology or computer has urged every discipline to disintegrate its conventional order for the post-modernism characterized by polysemous, diversified, obscure and sometimes, mutually contradicting elements, and as a result, animations had to find a new breakthrough in the conventional reality (cognitive and reflective reality). Thus, animations have been real enough to be perceived impromptu and emotionally, faster than the logical cognitive process beyond the simple technological barrier or the screen image processing. With such backgrounds in mind and by defining such a reality as 'sensuous reality', this study aimed to apply Gilles Deleuze's, reality of space to animation films and interpret it.