• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1581-1588
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• 2010

Most digital cameras use a single image sensor with Color Filter Array(CFA) for the advantage of costs and speed. The various color interpolation(demosaicing) algorithms are researched to reconstruct a full representation of the image. In this paper, we proposed a method of demosaicing about using weighted directional filter for vertical, horizontal, and diagonal direction edge. The method considered the efficiency of hardware resources for hardware implementation. The performance of proposed method was confirmed by comparing the conventional method in experiments using 24 Kodak test images. The proposed method was designed by Verilog HDL and was verified by using Virtex4 FPGA boards and CMOS Image Sensor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2779-2785
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• 2014

Edge Detection is a technique that obtains the particular information of the image using the brightness variation of pixel values and utilized for preprocessing in various image processing sectors. The conventional edge detection methods such as Sobel, Prewitt and Roberts are processed by applying the same weighted value to the entire pixels regardless of pixel distrbution and provides somewhat insufficient edge detection results. therefore, this paper has proposed an edge detection method considering the direction and magnitute of pixels by applying a modified directional mask.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1098-1110
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• 2003

In this paper, we propose a homomorphic wavelet-based MMSE filter with edge detection to restore images degraded by speckle noise. In the proposed method, a noisy image is first transformed into logarithmic domain. Each pixel in the transformed image is then classified into flat and edge regions by applying DIP operator to the image restored by homomorphic directional MMSE filter. Each pixel in flat region is restored by homomorphic wavelet-based MMSE filter. Each pixel in edge region is restored by the weighted sum of the output of homomorphic wavelet-based MMSE filtering and that of homomorphic directional MMSE filtering. The restored image in spatial domain is finally obtained by applying the exponential function to the restored image in logarithmic domain. Experimental results show that the restored images by the proposed method have ISNR improvement of 3.3-4.0 ㏈ and ${\beta}$, a measurement parameter on edge preservation, improvement of 0.0103-0.0126 and superior subjective image quality over those by conventional methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.256-264
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• 2012

The directional algebraic reconstruction technique (DART) using the trigonometric current pattern is one of the image reconstruction algorithms in electrical impedance tomography (EIT). This method needs to compute resistances between electrode pairs as using relation between the injected currents and measured voltages for the reconstruction of the inner image. The delay time is incurred in this process. Therefore this paper proposes modified directional algebraic reconstruction technique (mDART) using the adjacent current pattern instead of the trigonometric current pattern to solve the delay time for initial resistance values. The proposed method uses measured voltages instead of computed resistances in the reconstruction algorithm. Hence this method can eliminate the delay time because it does not use the resistances. In conclusion, the proposed method improves image quality and image reconstruction time by using the adjacent current pattern. To prove performance of the proposed method, we carried on computer simulation of various cases.

• Journal of Korea Multimedia Society
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• v.7 no.2
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• pp.164-172
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• 2004

Halftoning of gray-scale image is a process to produce a binary image. The error diffusion halftoning method produces high qualify binary image but that has some defects such as sharpening and directional artifacts. We propose the threshold modulation to reduce such defects. The proposed algorithm uses thresholds reflecting local characteristic of image. We calculate thresholds which minimize errors of flat region of each gray-scale level by using a linear gain between original image and error-diffused image and then represent edge by compensating thresholds in proportion to edge information. The proposed method improves on halftone quality by minimizing an error which cause sharpening and directional artifact.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.236-239
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• 1995

It is useful to simulate the human visual function for the purpose of image-processing. In this study, the hardware of the spatial filter with the sensitivity of lateral inhibition is realized by the combination of optical parts with electronic circuits. The diffused film with the characteristics of Gaussian type is prepared as a spatial filter. An object's image is convoluted with the spatial filter. From the difference of the convoluted images, the zero-cross position is detected at video rate. The edge of object is extracted in real-time by the use of this equipment. The resolution of edge changes with the value of the standard deviation of diffused film. In addition, it is possible to extract a directional edge selectively when the spatial filter with directional selectivity is used instead of Gaussian type of spatial filter.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.868-874
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• 2014

This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.437-445
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• 1999

Most autonomous mobile robots view only things in front of then, and as a result, they may collide with objects moving from the side or behind. To overcome this problem, an active omni-directional range sensor system has been built that can obtain an omni-directional depth map through the use of a laser conic plane and a conic mirror. In the navigation of the mobile robot, the proposed sensor system produces a laser conic plane by rotating the laser point source at high speed: this creates a two-dimensional depth map, in real time, once an image is captured. The results obtained from experiment show that the proposed sensor system is very efficient, and can be utilized for navigation of mobile robot in an unknown environment.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1329-1336
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• 2005

We propose an optimal edge detection algorithm adaptive to the various widths of edges. In order to construct this algorithm, we introduce an alternative definition of edge point and generalize the directional derivatives in the pixel space to obtain an extended directional derivatives beyond scaling. The result from applying our algorithm to a 2D image is analyzed comparing to that from the other algorithm.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.781-782
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• 2008

An object tracking system, which uses an omni-directional camera, is proposed in this work. First, we construct a mapping table, which describes the relationships between image coordinates and omni-directional angles Then, we develop a surveillance system to detect unexpected objects automatically from omni-directional images. Finally, we generate perspective views for detected objects by using the mapping table. Simulation results demonstrate that the proposed algorithm provides efficient performances.