• The Journal of the Acoustical Society of Korea
• /
• v.32 no.2
• /
• pp.147-156
• /
• 2013

In this paper, a new speech endpoint detection method in noisy environments for moving robot platforms is proposed. In the conventional method, the endpoint of speech is obtained by applying an edge detection filter that finds abrupt changes in the feature domain. However, since the feature of the frame energy is unstable in such noisy environments, it is difficult to accurately find the endpoint of speech. Therefore, a novel feature extraction method based on the twice-iterated fast fourier transform (TIFFT) and statistical models of speech is proposed. The proposed feature extraction method was applied to an edge detection filter for effective detection of the endpoint of speech. Representative experiments claim that there was a substantial improvement over the conventional method.

• Journal of the Institute of Convergence Signal Processing
• /
• v.13 no.4
• /
• pp.180-186
• /
• 2012

In this paper, a method of edge detection from low contrast and noisy images which contain hexagonal shape is proposed. This method is based on the combination of laplacian gaussian filter and an idea of filters which are dependent on the shape. First, an algorithm which has six masks as its extractors to detect the hexagonal edges especially in the comers is used. Here, two tricom filters are used to detect the tricom joints of hexagons and other four masks are used to enhance the line segments of hexagonal edges. As a natural image, a corneal endothelial cell image which usually has a regular hexagonal shape is selected. The edge detection of hexagonal shapes in this corneal endothelial cell is important for clinical diagnosis. Next, The proposal algorithm and other conventional methods are applied to noisy hexagonal images to evaluate each efficiency. As a result, this proposal algorithm shows a robustness against noises and better detection ability in the aspects of the signal to noise ratio, the edge coineidence ratio and the detection accuracy factor as compared with other conventional methods.

• Journal of the Institute of Convergence Signal Processing
• /
• v.15 no.4
• /
• pp.135-140
• /
• 2014

As the digital image devices are widely used, interests in the software- and the hardware-related image processing become higher and the image processing techniques are applied in various fields such as object recognition, object detection, fingerprint recognition, and etc. For the edge detections Sobel, Prewitt, Laplacian, Roberts and Canny detectors are used and these existing methods can excellently detect the edges of the images without noise. However, in the images corrupted by the impulse noise, these methods are insufficent in noise elimination characteristics, showing unsatisfactory edge detection. Therefore in this paper, in order to obtain excellent edge detection characteristics in the corrupted image by the impulse noise, an detection algorithm is porposed, which uses the central pixel of mask divided by four regions along the axis, calculates the estimated mask according to the representing pixel values in each regions, and detects the final edges by applying the estimates mask and the new directional one.

• Journal of the Korean Society of Radiology
• /
• v.9 no.2
• /
• pp.73-77
• /
• 2015

In order to observe the detailed structure of the detector, it was CT scanned to reproduce the detailed structure of the crystal shapes and traverse layer using the Monte Carlo calculation applying the detector model. The uncertainty of measurement was lowered by adjusting the detector core by the edge effect at a higher energy (400 keV or higher) through the offset of peak efficiency of the gamma ray at low energy. It was confirmed that there was the appropriate matching with spatial dependency using the PENELOPE calculation. That was achieved by adjusting the parameters describing the crystal core and rounding of edge and crystal core.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.38 no.8
• /
• pp.20-26
• /
• 2001

In this paper, the charge pump PLL using the dual PFD to improve the trade-off between acquisition behavior and locked behavior is proposed. This dual PFD consists of a positive edge triggered PFD and a negative edge triggered PFD. The proposed charge pump shows that it is possible to overcome the issue of the charge pump current imsmatch by the current subtraction circuit. Also, this charge pump can suppress reference spurs and disturbance of the VCO control voltage. The proposed charge pump PLL is simulated by SPICE using 0.25${\mu}m$ CMOS process parameters.

• Journal of Astronomy and Space Sciences
• /
• v.10 no.1
• /
• pp.86-93
• /
• 1993

We experiment of the method to obtain the uniform gas multiplication in multiwire proportional counter. The general techenique of anode wire connection for the high voltage supply could not secure the uniformity of multiplication because of the edge effect at the outer anode wires. We found that the variation of the multiplication could be corrected in the accuracy of $\pm$1.6% rms using the voltage compansation method.

• Korean Journal of Optics and Photonics
• /
• v.15 no.3
• /
• pp.258-262
• /
• 2004

The uncertainty of the detector-based candela scale is limited by the area measurement uncertainty of radiometric apertures. The apertures were fabricated with a diamond-turning machine which trimmed the edge of the apertures as sharply as a knife edge. The positions of the apertures were controlled by a digital feedback algorithm to scan the laser spot with the beam waist less than 5 ${\mu}{\textrm}{m}$. The knife edge scan yielded a set of coordinates on the edges of the aperture. The areas of the apertures were obtained by fitting the coordinates to the ellipses. The relative standard uncertainty of the measurement was estimated to be 8${\times}$10$^{-5}$.

• Journal of Digital Contents Society
• /
• v.13 no.2
• /
• pp.189-195
• /
• 2012

In this paper, face detection method in NIR(Near-InfraRed) images for human recognition is proposed. Edge histogram based on edge intensity and its direction, has been used to detect effectively faces on NIR image. The edge histogram descripts and discriminates face effectively because it is strong in environment of lighting change. SVM(Support Vector Machine) has been used as a classifier to detect face and the proposed method showed better performance with smaller features than in ULBP(Uniform Local Binary Pattern) based method.

• Journal of KIISE:Software and Applications
• /
• v.29 no.11
• /
• pp.809-817
• /
• 2002

This paper describes a new face detection method that is a pre-processing algorithm for on-line face recognition. To complement the weakness of using only edge or rotor features from previous face detection method, we propose the two types of face detection method. The one is a combined method with edge and color features and the other is a center area color sampling method. To prevent connecting the people's face area and the background area, which have same colors, we propose a new adaptive edge detection algorithm firstly. The adaptive edge detection algorithm is robust to illumination variance so that it extracts lots of edges and breakouts edges steadily in border between background and face areas. Because of strong edge detection, face area appears one or multi regions. We can merge these isolated regions using color information and get the final face area as a MBR (Minimum Bounding Rectangle) form. If the size of final face area is under or upper threshold, color sampling method in center area from input image is used to detect new face area. To evaluate the proposed method, we have experimented with 2,100 face images. A high face detection rate of 96.3% has been obtained.

• The Korean Journal of Applied Statistics
• /
• v.32 no.5
• /
• pp.721-740
• /
• 2019

Noise reduction is an important field in image processing and requires a statistical approach. However, it is difficult to assume a specific distribution of noise, and a spatial filter that reflects regional characteristics is a small sample and cannot be accessed in a parametric manner. The first order image differential and the second order image differential show a clear difference according to the noise level included in the image and can be more clearly understood using the canyon edge detector. The Fligner-Killeen test was performed and the bootstrap method was used to statistically check the noise level. The estimated noise level was set between 0 and 1 using the cumulative distribution function of the beta distribution. In this paper, we propose a nonparametric noise reduction algorithm that accounts for the noise level included in the image.