• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.05a
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• pp.861-864
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• 2009

Recently, the biometric recognition technology of veins in different parts of hand is very active. In this paper the image hierarchical slicing provides a way to detect vein patterns. The scanned vein image will be sliced into various thicknesses. We first get the average brightness values of the sliced image and then convert them into curvature where we can detect candidates of the vein. The candidates of the vein are used to do a further analysis. We search all of the vein candidates and analyze them to get the real vein pattern in the overlapping extraction. We propose this novel algorithm to detect the vein pattern from the original image.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.664-670
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• 2007

This study deals with image-based visual servoing for automatic recharging of mobile robot. Because mobile robot must be recharged periodically, it is necessary to detect and move to docking station. Generally, laser scanner is used for detect of position of docking station. CCD Camera is also used for this purpose. In case of using cameras, the position-based visual servoing method is widely used. But position-based visual servoing method requires the accurate calibration and it is hard and complex work. Another method using cameras is image-based visual servoing. Recently, image based visual servoing is widely used for robotic application. But it has a problem that cannot have linear trajectory in the 3-dimensional space. Because of this weak point, image-based visual servoing has a limit for real application. In case of 2-dimensional movement on the plane, it has also similar problem. In order to solve this problem, we point out the main reason of the problem of the resolved rate control method that has been generally used in the image-based visual servoing and we propose an image-based visual servoing method that can reduce the curved trajectory of mobile robot in the cartesian space.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.220-228
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• 2022

Image always carry useful information, detecting a text from scene images is imperative. The proposed work's purpose is to recognize scene text image, example boarding image kept on highways. Scene text detection on highways boarding's plays a vital role in road safety measures. At initial stage applying preprocessing techniques to the image is to sharpen and improve the features exist in the image. Likely, morphological operator were applied on images to remove the close gaps exists between objects. Here we proposed a two phase algorithm for extracting and recognizing text from scene images. In phase I text from scenery image is extracted by applying various image preprocessing techniques like blurring, erosion, tophat followed by applying thresholding, morphological gradient and by fixing kernel sizes, then canny edge detector is applied to detect the text contained in the scene images. In phase II text from scenery image recognized using MSER (Maximally Stable Extremal Region) and OCR; Proposed work aimed to detect the text contained in the scenery images from popular dataset repositories SVT, ICDAR 2003, MSRA-TD 500; these images were captured at various illumination and angles. Proposed algorithm produces higher accuracy in minimal execution time compared with state-of-the-art methodologies.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1340-1343
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• 1996

In this study, we developed the drowziness prevention system to detect the driver's drowziness and relieve the driver. A computer vision method was proposed to detect the driver's drowziness. We extracted the eyes and mouth in the face image and tracked the positions from the image sequencies in real time. The eye blink duration and yawning was used as the parameters of drowziness. Wehn the drowziness state of a driver is detected, the driver is refreshed by the scent generator and the alarm. Also, the driver's bio-signal is acquired and analysed the vigilance state.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.347-350
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• 2003

In this paper, a new automated defects detection method for a TFT-LCD panel is presented. An input image is preprocessed to lessen small abnormal noises and non-uniformity of the image. The adaptive multi-thresholds are used to detect Muras, which are the major defects occurred on TFT-LCD panels. Those are determined adaptively depending on the brightness and the brightness distribution of a local block. For the synthetic images and real Mura images, the proposed algorithm can effectively detect Muras in a reasonable time.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.10
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• pp.130-138
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• 1996

In this paper, we propose a neural network which detect edges of different orentation and spatial frequency in arbitrary image data. We constructed the proposed neural network iwth two different types neural network. A diffusion network performs the gaussian operation efficiently by the diffusion process. And the spatial difference network has specially designed connections suitble to detect the contours of a specific oriention. Simulation results showed that the proposed neural network can extract the edges of selected orientation efficiently by applying the neural network to a test pattern and the real image.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.9 s.351
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• pp.38-43
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• 2006

In this paper, we propose the efficient dead pixel detection algorithm for CMOS image sensors and its hardware architecture. The CMOS image sensors as image input devices are becoming popular due to the demand for miniaturized, low-power and cost-effective imaging systems. However, the presence of the dead pixels degrade the image quality. To detect the dead pixels, the proposed algorithm is composed of scan, trace and detection step. The experimental results showed that it could detect 99.99% of dead pixels. It was designed in a hardware description language and total logic gate count is 3.2k using 0.25 CMOS standard cell library.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.2
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• pp.90-98
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• 2015

This research propose with image-based visual a new approach to design a feedback control of mobile robot. because mobile robot must be recharged periodically, it is necessary to detect and move to docking station. Generally, laser scanner is used for detect of position of docking station. CCD Camera is also used for this purpose. In case of using camera, the position-based visual servoing method is widely used. But position-based visual servoing method requires the accurate calibration and it is hard and complex work. Another method using cameras is inmage-based visual feedback. Recently, image based visual feedback is widely used for robotic application. But it has a problem that cannot have linear trajectory in the 3-dimensional space. Because of this weak point, image-based visual servoing has a limit for real application. in case of 2-dimensional movement on the plane, it has also similar problem. In order to solve this problem, we point out the main reason of the problem of the resolved rate control method that has been generally used in the image-based visual servoing and we propose an image-based visual feedback method that can reduce the curved trajectory of mobile robot in th cartesian space.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.549-555
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• 2006

An edge detection is an very important area in image processing and computer vision, General edge detection methods (Robert mask, Sobel mask, Kirsh mask etc) are a good performance to detect step edge in a image but are no good performance to detect step edge in a noses image. We suggested a step edge detection method based on image information measure and neutral network. Using these essential properties of step edges, which are directional and structural and whose gray level distribution in neighborhood, as a input vector to the BP neutral network we get the good result of proposed algorithm. And also we get the satisfactory experimental result using rose image and cell images an experimental and analysing image.