• Journal of Information Processing Systems
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• v.10 no.2
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• pp.283-299
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• 2014

Skin detection is used in many applications, such as face recognition, hand tracking, and human-computer interaction. There are many skin color detection algorithms that are used to extract human skin color regions that are based on the thresholding technique since it is simple and fast for computation. The efficiency of each color space depends on its robustness to the change in lighting and the ability to distinguish skin color pixels in images that have a complex background. For more accurate skin detection, we are proposing a new threshold based on RGB and YUV color spaces. The proposed approach starts by converting the RGB color space to the YUV color model. Then it separates the Y channel, which represents the intensity of the color model from the U and V channels to eliminate the effects of luminance. After that the threshold values are selected based on the testing of the boundary of skin colors with the help of the color histogram. Finally, the threshold was applied to the input image to extract skin parts. The detected skin regions were quantitatively compared to the actual skin parts in the input images to measure the accuracy and to compare the results of our threshold to the results of other's thresholds to prove the efficiency of our approach. The results of the experiment show that the proposed threshold is more robust in terms of dealing with the complex background and light conditions than others.

• Journal of Advanced Navigation Technology
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• v.20 no.5
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• pp.496-502
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• 2016

In this paper, we proposed and implemented a GUI-based system to recognize and record measured values of digital instruments in the industrial site through image processing. Unlike the existing vehicle license plate recognition system, the measured values of the measuring instrument are displayed on the LCD screen as digital numbers. So, the proposed system considers the decimal point, a negative sign, light reflected by LCD protective glass, and various disturbance factors. We used blob-labeling technique to recognize the numbers displayed on the LCD screen, the recognized number images were determined as certain numbers through the template matching, and recognized values were recorded in the storage device with measurement time. Therefore, the proposed system in this paper would reduce the burden of writing when recording the measured values of the inside/outside diameter or height of the product in the industrial site, so effective and errorless process management in production process is possible by preventing errors in recording measurements when written by hand.

• The Journal of Korean Association of Computer Education
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• v.13 no.4
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• pp.77-86
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• 2010

In this paper, we propose a real time post-processing visual enhancement technique to reduce the blocking artifacts in block based DCT decoded image for mobile devices that have allocation of the restricted resource. In order to reduce the blocking artifacts effectively even while preserving the image edge to the utmost, the proposed algorithm uses the deblocking filtering or the directional filtering according to the edge detection of the each pixel. After it is discriminated that the pixel to apply the deblocking filtering belongs again to the monotonous area, the weighted average filter with the adaptive mask is applied for the pixel to remove the blocking artifacts. On the other hand, a new directional filter is utilized to get rid of staircase noise and preserve the original edge component. Experimental results show that the proposed algorithm produces better results than those of the conventional algorithms in both subjective and objective qualities.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.24 no.4
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• pp.599-607
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• 2000

In this study, experiments have been performed to examine the effects of background gray-level on the depth-of-field and on the in-focus criteria. The normalized value of contrast(VC) and the gradient indicator(GI) were used as the in-focus criteria for the small and the large size-ranges of particles, respectively. The slightly larger number of pixels were detected with the brighter background. The maximum of the normalized value of contrast(VCmax) is decreased with the brighter background and its deviation from that with the background gray-level of 160 turned out to be about $pm$15% when the background gray-level changes from 100 to 200. However, the maximum gradient indicator(GImax) changes with the background gray-level within only $pm$5%. The depth-of-field for the VC-applicable particle-size range is largely dependent on the background gray-level. On the other hand, the depth-of-field for the GI-applicable particle-size range changes only slightly with the background gray-level. To keep the normalized standard deviation of the particle size within 0.1, the background gray-level should be set 160$pm$20 for both the VC-applicable and GI-applicable ranges which cover the particle size between $10{\mu}m$ and $300{\mu}m$.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.47 no.4
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• pp.47-54
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• 2010

We propose a smart human-computer interface replacing conventional mouse interface. The interface is able to control cursor and command action with only hand performing without object. Four finger motions(left click, right click, hold, drag) for command action are enough to express all mouse function. Also we materialize cursor movement control using image processing. The measure what we use for inference is entropy of EMG signal, gaussian modeling and maximum likelihood estimation. In image processing for cursor control, we use color recognition to get the center point of finger tip from marker, and map the point onto cursor. Accuracy of finger movement inference is over 95% and cursor control works naturally without delay. we materialize whole system to check its performance and utility.

• The KIPS Transactions:PartB
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• v.16B no.5
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• pp.347-358
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• 2009

In this thesis, we develop a vision based hand motion recognition system using a camera with two rotational motors. Existing systems were implemented using a range camera or multiple cameras and have a limited working area. In contrast, we use an uncalibrated camera and get more wide working area by pan-tilt motion. Given an image sequence provided by the pan-tilt camera, color and pattern information are integrated into a tracking system in order to find the 2D position and direction of the hand. With these pose information, we estimate 3D motion plane on which the gesture motion trajectory from approximately forms. The 3D trajectory of the moving finger tip is projected into the motion plane, so that the resolving power of the linear gesture patterns is enhanced. We have tested the proposed approach in terms of the accuracy of trace angle and the dimension of the working volume.

• The KIPS Transactions:PartB
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• v.10B no.2
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• pp.151-156
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• 2003

The vergence control method is presented for a parallel-axls stereo camera (PASC) using a signal processing technique such as shift, (rotation), and scaling. The PASC is considered as the simplest one of binocular stereo cameras. However, its major limitation lies in the controllability of vergence since its left and right imaging sensors of CCDs are fixed. On the other hand, a horizontal-moving-axis stereo camera (HMASC) with movable imaging sensors is able to control the vergence by moving its CCDs horizontally. In spite of its vergence controllability, there is a major drawback in the implementation because of complicated mechanical structure and the additional cost. To overcome the vergence control problem of the PASC, an operational principle of the HMASC is applied to the PASC. To be specific, without any additional hardware the vergence control problem of the PASC is solved with the signal processing technique. Assuming the virtual displacement between CCD's, a disappearing part of acquired images is removed and the original image site is recovered via interpolation. Experimental results show that the vergence control between stereo images captured by the PASC it possible with an acceptable degradation of the image quality defending on the virtual displacement of CCDs.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.383-394
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• 2018

In this paper, we investigate image and video compression techniques based on deep learning which are actively studied recently. The deep learning based image compression technique inputs an image to be compressed in the deep neural network and extracts the latent vector recurrently or all at once and encodes it. In order to increase the image compression efficiency, the neural network is learned so that the encoded latent vector can be expressed with fewer bits while the quality of the reconstructed image is enhanced. These techniques can produce images of superior quality, especially at low bit rates compared to conventional image compression techniques. On the other hand, deep learning based video compression technology takes an approach to improve performance of the coding tools employed for existing video codecs rather than directly input and process the video to be compressed. The deep neural network technologies introduced in this paper replace the in-loop filter of the latest video codec or are used as an additional post-processing filter to improve the compression efficiency by improving the quality of the reconstructed image. Likewise, deep neural network techniques applied to intra prediction and encoding are used together with the existing intra prediction tool to improve the compression efficiency by increasing the prediction accuracy or adding a new intra coding process.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.3
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• pp.1-12
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• 2011

Large-sized multi-touch screen is usually made using infrared rays. That is because it has technical constraints or cost problems to make the screen with the other ways using such as existing resistive overlays, capacitive overlay, or acoustic wave. Using infrared rays to make multi-touch screen is easy, but is likely to have technical limits to be implemented. To make up for these technical problems, two other methods were suggested through Surface project, which is a next generation user-interface concept of Microsoft. One is Frustrated Total Internal Reflection (FTIR) which uses infrared cameras, the other is Diffuse Illumination (DI). FTIR and DI are easy to be implemented in large screens and are not influenced by the number of touch points. Although FTIR method has an advantage in detecting touch-points, it also has lots of disadvantages such as screen size limit, quality of the materials, the module for infrared LED arrays, and high consuming power. On the other hand, DI method has difficulty in detecting touch-points because of it's structural problems but makes it possible to solve the problem of FTIR. In this thesis, we study the algorithms for effectively correcting the distort phenomenon of optical lens, and image processing algorithms in order to solve the touch detecting problem of the original DI method. Moreover, we suggest calibration algorithms for improving the accuracy of multi-touch, and a new tracking technique for accurate movement and gesture of the touch device. To verify our approaches, we implemented a table-based multi touch screen.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.6
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• pp.463-470
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• 2022

Intravenous injection is widely used for patient treatment, including injection drugs, fluids, parenteral nutrition, and blood products, and is the most frequently performed invasive treatment for inpatients, including blood collection, peripheral catheter insertion, and other IV therapy, and more than 1 billion cases per year. Intravenous injection is one of the difficult procedures performed only by experienced nurses who have been trained in intravenous injection, and failure can lead to thrombosis and hematoma or nerve damage to the vein. Nurses who frequently perform intravenous injections may also make mistakes because it is not easy to detect veins due to factors such as obesity, skin color, and age. Accordingly, studies on auxiliary equipment capable of visualizing the venous structure of the back of the hand or arm have been published to reduce mistakes during intravenous injection. This paper is about the development of venous detection equipment that visualizes venous structure during intravenous injection, and the optimal combination was selected by comparing the brightness of acquired images according to the combination of near-infrared (NIR) LED and Filter with different wavelength bands. In addition, an image processing algorithm was derived to threshehold and making blood vessel part to green through grayscale conversion, histogram equilzation, and sharpening filters for clarity of vein images obtained through the implemented venous detection experimental module.