• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1244-1248
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• 2005

In this paper, we propose fuzzy c-means (FCM) to solve recognition errors in invariant range image, multi-pose face recognition. Scale, center and pose error problems were solved using geometric transformation. Range image face data was digitized into range image data by using the laser range finder that does not depend on the ambient light source. Then, the digitized range image face data is used as a model to generate multi-pose data. Each pose data size was reduced by linear reduction into the database. The reduced range image face data was transformed to the gradient face model for facial feature image extraction and also for matching using the fuzzy membership adjusted by fuzzy c-means. The proposed method was tested using facial range images from 40 people with normal facial expressions. The output of the detection and recognition system has to be accurate to about 93 percent. Simultaneously, the system must be robust enough to overcome typical image-acquisition problems such as noise, vertical rotated face and range resolution.

• Journal of the Korea Society of Computer and Information
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• v.21 no.11
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• pp.23-30
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• 2016

In this paper, we propose an adaptive histogram projection technique for dynamic range compression and an efficient detail enhancement method which is enhancing strong edge while reducing noise. First, The high dynamic range image is divided into low-pass component and high-pass component by applying 'guided image filtering'. After applying 'guided filter' to high dynamic range image, second, the low-pass component of the image is compressed into 8-bit with the adaptive histogram projection technique which is using global standard deviation value of whole image. Third, the high-pass component of the image adaptively reduces noise and intensifies the strong edges using standard deviation value in local path of the guided filter. Lastly, the monitor display image is summed up with the compressed low-pass component and the edge-intensified high-pass component. At the end of this paper, the experimental result show that the suggested technique can be applied properly to the IR images of various scenes.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.9
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• pp.1448-1455
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• 1990

In this paper, a range image segmentation method is proposed. This method consists of an initial segmentation stage by discontinuous edge detection and surface type labeling based on the sign of the principal curvatures. Initially type labeled image is oversegmented, this image is merged via stepwise optimal region merging stage based on polynomial function approxiamtion. The successful segmentation results are presented for two synthetic range images with noise and a real-world ERIM range image.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• Journal of Broadcast Engineering
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• v.14 no.4
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• pp.428-437
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• 2009

A high dynamic range (HDR) image can represent real world scenes that have a wide range of luminance intensity. However, compared with the range of real world luminance, conventional display devices have a low dynamic range (LDR). To display HDR images onto conventional displayable devices such as monitors and printers, we propose the logarithmic based global reproduction algorithm that considers the features of the image using reproduction parameters. Based on the characteristics of the image, we first modify the input luminance values for reproducing perceptually tuned images and then obtain the displayable output values directly. The experimental results show that the proposed algorithm achieves good subjective results while preserving details of the image; furthermore, the proposed algorithm has a fast, simple and practical structure for implementation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4C
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• pp.350-357
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• 2010

In this paper, we present an auto-range fast bilateral filter (FBF) for high-dynamic-range (HDR) images, which increases computation speed by using adaptive standard deviations for range filter (RF) of FBF in iCAM06. Many images that cover the entire dynamic range of the scene with different exposure times are fused into one High Dynamic Range (HDR) image. The representative algorithm for HDR image rendering is iCAM06, which is based on the iCAM framework, such as the local white point adaptation, chromatic adaptation, and the image processing transform (IPT) uniform color space. FBF in iCAM06 uses constant standard deviation in RF. So, it causes unnecessary FBF computation in high stimulus range with broad and low distribution. To solve this problem, the low stimulus image and high stimulus image of CIE tri-stimulus values (XYZ) divided by the threshold are respectively processed by adaptive standard deviation based on its histogram distribution. Experiment results show that the proposed method reduces computation time than the previous FBF.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.6
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• pp.117-124
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• 2008

The approaches to overcome the limited spatial resolution and the limited dynamic range of image sensors have been studied independently. A high resolution image is reconstructed from multiple low resolution observations and a wide dynamic range image is reconstructed from differently exposed multiple low dynamic range in es based on signal processing approach. In practical situations, it is reasonable to address them in a unified context because the recorded image suffers from limitations of both spatial resolution and dynamic range. In this paper, the image acquisition process including limited spatial resolution and limited dynamic range is modelled. With the image acquisition model, the response function of the imaging system is estimated and the single image of which spatial resolution and dynamic range are simultaneously enhanced is obtained. Experimental results indicate that the proposed algorithm outperforms the conventional approaches that perform the high resolution and wide dynamic range reconstruction sequentially with respect to both objective and subjective criteria.

• Agricultural and Biosystems Engineering
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• v.3 no.1
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• pp.35-43
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• 2002

The spectral color resolution of an image is very important in color image analysis. Two factors influencing the spectral color resolution of an image are illumination intensity and lens aperture for a selected vision system. An optimal combination of illumination intensity and lens aperture for color image analysis was determined in the study. The method was based on a model of dynamic range defined as the absolute difference between digital values of selected foreground and background color in the image. The role of illumination intensity in machine vision was also described and a computer program for simulating the optimal combination of two factors was implemented for verifying the related algorithm. It was possible to estimate the non-saturating range of the illumination intensity (input voltage in the study) and the lens aperture by using a model of dynamic range. The method provided an optimal combination of the illumination intensity and the lens aperture, maximizing the color resolution between colors of interest in color analysis, and the estimated color resolution at the combination for a given vision system configuration.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.299-302
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• 1995

Recently, we proposed a 3-D range-image measuring system for a slowly moving object by mechanically scanning a laser light beam emitted from a self mixing laser diode. In this paper, we introduced that every object moves along a straight line course, which is set diagonally against the semiconductor laser beam so that we can recognize each shape and size parameters of objects separately from the acquired 3-D range-image. We measured a square mesa on a square plane as an object. The measured velocity was 4.44mm/s and 4.63mm/s with an error of 0.56mm/s to 0.37mm/s. And thickness error of the mesa was 0.5mm to 0.6mm, which was obtained from the 3-D range-image of the standstill or moving object with thickness of 17.Omm.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.154-157
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• 2009

High dynamic range image can describe the real world scenes that have a wide range of luminance intensity. To display high dynamic range (HDR) image into conventional displayable devices such as monitors and printers, we proposed the logarithmic based global mapping algorithm that consider the features of image using mapping parameters. Based on characteristics of image, we first modify input luminance values for reproducing perceptually tuned images and then displayable output values are obtained directly. The experimental results show that the proposed algorithm achieves good subjective results while preserving details of image, furthermore proposed algorithm has fast simple and practical structure for implementation.