• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1367-1370
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• 1987

This paper describes a new automatic bi-level image segmentation algorithm which determines local thresholds by applying a locally adaptive edge detection technique to a variable threshold selection method. Computer simulations show that the performance of the proposed algorithm is more robust than those of automatic global thresholding methods.

• 한국정보디스플레이학회:학술대회논문집
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• 2002.08a
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• pp.849-851
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• 2002

This research describes a image-processing technique for the scratch detecting algorithm for ITO coated glass. We use the modified logical thresholding method for binarization of gray-scale glass image. This method is useful to the algorithm for detecting the scratch of ITO coated glass automatically without need of any prior information of manual fine-tuning of parameters.

• The Journal of Natural Sciences
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• v.4
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• pp.191-220
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• 1991

A new texture segmentation-based image coding technique which performs segmentation based on roughness of textural regions and properties of the human visual system (HVS) is presented. This method solves the problems of a segmentation-based image coding technique with constant segments by proposing a methodology for segmenting an image texturally homogeneous regions with respect to the degree of roughness as perceived by the HVS. The fractal dimension is used to measure the roughness of the textural regions. The segmentation is accomplished by thresholding the fractal dimension so that textural regions are classified into three texture classes; perceived constant intensity, smooth texture, and rough texture. An image coding system with high compression and good image quality is achieved by developing an efficient coding technique for each segment boundary and each texture class. For the boundaries, a binary image representing all the boundaries is created. For regions belonging to perceived constant intensity, only the mean intensity values need to be transmitted. The smooth and rough texture regions are modeled first using polynomial functions, so only the coefficients characterizing the polynomial functions need to be transmitted. The bounda-ries, the means and the polynomial functions are then each encoded using an errorless coding scheme. Good quality reconstructed images are obtained with about 0.08 to 0.3 bit per pixel for three different types of imagery ; a head and shoulder image with little texture variation, a complex image with many edges, and a natural outdoor image with highly textured areas.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.669-681
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• 2018

CNN (Convolution Neural Network) is one of the most important techniques to identify the kind of objects in the captured pictures. Whereas the conventional models have been used for low resolution images, the technique to recognize the high resolution images becomes crucial in the field of artificial intelligence. In this paper, we proposed an efficient CNN model based on dilated convolution and thresholding techniques to increase the recognition ratio and to decrease the computational complexity. The simulation results show that the proposed algorithm outperforms the conventional method and the thresholding technique enhances the performance of the proposed model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.10
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• pp.1469-1482
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• 1993

A new image coding technique has been proposed based on the wavelet transform. To achieve lower ceding rates and good qualities in reconstructed images, some of wavelet coefficients were removed by thresholding and quantized in accordance with the sensitivity of the human visual system(HVS). For each block of subimages in wavelet transform domain, block thresholding scheme has been used to remove the unimportant wavelet coefficients according to the frequency characteristic and statistical property of wavelet coefficients. The location information of quantized blocks and removed blocks were encoded using run-length coder which is effective for the exponential distribution. Quantized coefficients were encoded using variable length coder which matches well to their distribution. Simulation results show that the reconstructed images maintain high quality with the low bit rate, below 1.0 bits per pel.

• 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 Korea Multimedia Society
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• v.19 no.2
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• pp.200-208
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• 2016

Compressed sensing is a signal processing technique for efficiently acquiring and reconstructing in an under-sampled (i.e., under Nyquist rate) representation. A block compressed sensing with projected Landweber (BCS-SPL) framework is most widely known, but, it has high computational complexity at decoder side. In this paper, by introducing adaptive exit criteria instead of fixed exit criteria to SPL framework, an effective fast algorithm is designed in such a way that it can utilize efficiently the sparsity property in DCT coefficients during the iterative thresholding process. Experimental results show that the proposed algorithm results in the significant reduction of the decoding time, while providing better visual qualities than conventional algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.8
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• pp.914-916
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• 2016

The noise in a power signal degrades the detection rate of the power quality (PQ) event signals. We present a new wavelet de-noising technique for PQ event detection that employs the correlation-based thresholding instead of the wavelet-scale-based thresholding of existing schemes. The simulation results show that the proposed scheme is more robust to Gaussian and impulsive noisy conditions and has further improved detection ratio than existing schemes.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.330-339
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• 2015

Power quality (PQ) problems are becoming a big issue, since delicate complex electronic devices are widely used. We present a new denoising technique using discrete wavelet transform (DWT), where a modified correlation thresholding is used in order to reliably detect the PQ disturbances. We consider various PQ disturbances on the basis of IEEE-1159 standard over noisy environments, including voltage swell, voltage sag, transient, harmonics, interrupt, and their combinations. These event signals are decomposed using DWT for the detection of disturbances. We then evaluate the PQ disturbance detection ratio of the proposed denoising scheme over Gaussian noise channels. Simulation results also show that the proposed scheme has an improved signal-to-noise ratio (SNR) over existing scheme.

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.1173-1178
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• 2003

Recently, Organic EL(Electro Luminescence) is interested in Flat Panel Display(FPD) department of new generation. This paper describes a image processing algorithm for the scratch detecting for ITO coated glass. We use the logical level thresholding method for binarization of gray-scaled glass image. This method is useful to the algorithm for detecting scratch of ITO coated glass automatically without need of any prior information of manual fine tuning of parameters.