• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.7
• /
• pp.1479-1486
• /
• 2011

In this paper, a simple and robust algorithm is proposed for detecting straight line segments in a steel plate image. Line detection from a steel plate image is a fundamental task for analyzing and understanding of the image. The proposed algorithm is based on small eigenvalue analysis. The proposed approach scans an input edge image from the top left comer to the bottom right comer with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Before calculating the eigenvalue, each line segment is separated from the edge image where several line segments are overlapped to increase the accuracy of the line detection. Additionally, unnecessary line segments are eliminated by the number of pixels and the directional information of the detected line edges. The respects of the experiments emphasize that the proposed algorithm outperforms the existing algorithm which uses small eigenvalue analysis.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.17 no.9
• /
• pp.2199-2205
• /
• 2013

In modern society the image processing has been applied to various digital devices such as smartphone, digital camera, and digital TV. In the field of image processing the edge detection is one of the important parts in the image processing procedure. The image edge means point that the pixel value is changed between background and object rapidly, and includes the important information such as magnitude, location, and orientation. The performance of the existing edge detection method is insufficient for the image degraded by AWGN(additive white Gaussian noise) because it detects edges by using small weighted masks. Therefore, in this paper, to detect edge in AWGN environment effectively, we proposed an algorithm that detects edge as calculated gradient of sorting vector which is transformed by estimated mask from new pixel according to each region.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.12
• /
• pp.2975-2980
• /
• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. Detect this edge has been conducted in various fields at domestic and international. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, to complement this, preprocessing using gray-level transformation function and algorithm finding final edge using maximum and minimum value of estimated mask by local mask are proposed. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.10
• /
• pp.2441-2449
• /
• 2015

In this digital information era, utilization of images are essential for various media, and the edge is an important characteristical information of an object in images that includes the size, location, direction and etc. Many domestic and international studies are being conducted in order to detect these edge. Existing edge detection methods include Sobel, Prewitt, Roberts, Laplacian, LoG and etc. which apply fixed weight value. As these existing edge detection methods apply fixed weight mask to the image, edge detection characteristic appears slightly insufficient. Accordingly, in order to supplement these problems, this study used bottom-hat transformation from mathematical morphology and opening operation in improving the image and proposed an algorithm that detects for the edge after calculating mask-based gradient. And to evaluate the performance of the proposed algorithm, a comparison was made against the existing Sobel, Roberts, Prewitt, Laplacian, LoG edge detection methods, in illustrating visual images, and similarities were compared by calculating the MSE value based on the standard of each image.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.18 no.1
• /
• pp.47-56
• /
• 1993

In this paper, pyramidal VQ image coding by DCT classifier based on HVS is studied. The proposed DCT classifier based on HVS is that the transform subblocks of the image are mlultiplied by MTF which is a sort of band pass filter and sorted by the magnitude of their ac energy levels and classifeid into three classes such as low, middle and high variance class by the threshold and then edges are detected in comparison of the energy sum of ac transform coefficients corresponding to the different edge directions.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.3C
• /
• pp.278-286
• /
• 2007

In this paper, an efficient algorithm is proposed for the interpolation of interlaced images. First of all, by efficiently estimating the directional spatial correlations of neighboring pixels, increased interpolation accuracy can be achieved. And then using the gradient vector which was obtained by Sobel operation, enables to consider the fine directional edges and make it possible to estimate the accurate direction of edges. In other words, it is possible to interpolate the interlaced images with considering the characteristics of images. In addition, by altering the conventional edge detector for the purpose of a easy De-interlacing and multiplying the optimal translation coefficients to each of the gradient vectors, an efficient interpolation for images can be achieved. Comparing with the conventional De-interlacing algorithms, proposed algorithm not only reduced the complexity but also estimated the accurate edge direction and the proposed scheme have been clearly verified that it enhances the objective and subjective image quality by the extensive simulations for various images.

• Journal of Broadcast Engineering
• /
• v.17 no.2
• /
• pp.316-324
• /
• 2012

In this paper, a novel descreening method using HOG(histogram of gradient)-based adaptive smoothing filter is proposed. Conventional edge-oriented smoothing methods does not provide enough smoothing to the halftone image due to the edge-like characteristic of the halftone noise. Moreover, clustered-dot halftoning method, which is commonly used in printing tends to create Moire pattern because of the intereference in color channels. Therefore, the proposed method uses HOG to distinguish edges and the amount of smoothing to be performed on the halftone image is then calculated according to the magnitude of the HOG in the edge and edge normal orientation. The proposed method was tested on various scanned halftone materials, and the results show that it effectively removes halftone noises as well as Moire pattern while preserving image details.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.45 no.3
• /
• pp.37-45
• /
• 2008

Quality assessment ai s to evaluate if a distorted image or video has a good quality by measuring the difference between the original and distorted images or videos. In this paper, to assess the visual qualify of a distorted image or video, visual features of the distorted image are compared with those of the original image instead of the direct comparison of the distorted image with the original image. We use edge projections from two images as features, where the edge projection can be easily obtained by projecting edge pixels in an edge map along vertical/horizontal direction. In this paper, edge projections are obtained by using vertical/horizontal directions of gradients as well as the magnitude of each gradient. Experimental results show the effectiveness of the proposed quality assessment through the comparison with conventional quality assessment algorithms such as structural similarity(SSIM), edge peak signal-to-noise ratio(EPSNR), and edge histogram descriptor(EHD) methods.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.18 no.1
• /
• pp.210-216
• /
• 2014

The edge in the image is a part which the brightness changes rapidly between the object and the object or objects and background, and includes information of the features such as size, position, orientation, and texture of the object. The edge detection is the technique that acquires these information of the images, and now the researches to detect edges are making steady progress. Typical conventional edge detection methods are Sobel, Prewitt, Roberts using the first derivative operator and Laplacian method using the second derivative operator and so on. These methods is more or less insufficient that the characteristics of the edge detection in the image added salt and pepper noise. therefore, in this paper, an edge detection algorithm using modified mask that applies different size mask according to noise density of local mask is proposed.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.7 no.5
• /
• pp.1033-1039
• /
• 2012

In this paper, a simple and robust algorithm is proposed for detecting each steel plate from a image which contains several steel plates. Steel plate is characterized by line edge, so line detection is a fundamental task for analyzing and understanding of steel plate images. To detect the line edge, the proposed algorithm uses the small eigenvalue analysis. The proposed approach scans an input edge image from the top left corner to the bottom right corner with a moving mask. A covariance matrix of a set of edge pixels over a connected region within the mask is determined and then the statistical and geometrical properties of the small eigenvalue of the matrix are explored for the purpose of straight line detection. Using the detected line edges, each plate is determined based on the directional information and the distance information of the line edges. The results of the experiments emphasize that the proposed algorithm detects each steel plate from a image effectively.