• Journal of Broadcast Engineering
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• v.17 no.2
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• pp.316-324
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• 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 Korean Graphic Arts Communication Society
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• v.15 no.2
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• pp.57-76
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• 1997

A color halftoning is the process of generating halftone images for the different color plans, for example, cyan, magenta, yellow, and black for a offset printing device. A conventional halftone technique, so called AM screening, is simple and easy to implement, but the halftoned dot patterns by using this method is not free for the moire` fringe. Moire` patterns are caused the power spectrum distribution on low spatial frequency domain. To avoid Moire` patterns, the conventional screen require the different screen angles for each color plans. Recently, Ultra-fine and 7 color printing methods are developed to expend the color gamut. In 7 color printing method must be used the halftone technique of random and blue noise characteristic to avoid Moire` fringe.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.465-467
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• 1992

This paper shows 3D vision system based on halftone image analysis. Any halftone image has its own surface vector normal to surface patch. To classily the given 3D images, all the patch on 3D object are transformed to black/white halftone. First we extract the general learning patterns which represents required slopes and their attributes. And next we propose 3D segmentation by searching intensity, slope and density. Artificial neural network is found to be very suitable in this approach, because it has powerful learning quality and noise tolerant. In this study, 3D shape reconstruct using pyramidian model. Our results are evaluated to enhance the quality.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.6
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• pp.27-34
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• 2009

Block truncation coding (BTC) is a simple and efficient image compression technique. However, it yields images of unacceptable quality and significant blocking effects are seen when the block size is increasing. Ordered dither block truncation coding (ODBTC) was proposed to solve above problem maintaining the same compression capability. In this paper, we propose a data hiding method which can be applied to halftone images. EMD was developed by Zhang and Wang [6] for data hiding in the grayscale image. Therefore, EMD is not proper for bitmap images. In this paper, we show that EMD can be used to apply bitmap halftone image. In our experiments, we prove that our method is efficient in a halftone image.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.10
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• pp.72-82
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• 1999

The error diffusion algorithm is excellent for reproducing continuous gray-scale images to bianry images and also has good edge characteristics. However, it is well known that artifacts with objectionable patterns can occur in the halftoned images. On the other hand, a halftone algorithm using blue noise mask has been proposed. where the halftoning is achieved by a pixelwise comparison of gray-scale image with an array, the blue noise mask. It doesn't have pattern artifacts, but the halftoned image looks unclear because the quantization errors are not feedbacked compared to the error diffusion. In this paper, edge enhanced error diffusion which dithers the threshold with the blue noise mask is proposed. We show that the proposed algorithm can produce unstructured and edge enhanced halftone images. This algorithm is analyzed by the concept of an equivalent input image. The performace of the proposed algorithm is compared with that of the conventional halftoning by measuring the radially averaged power spectrum and edge correlation.

• Journal of KIISE:Software and Applications
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• v.35 no.3
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• pp.162-168
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• 2008

A look-up table based vector adaptive filter is proposed in color inverse halftoning. Inverse halftoning converts halftone image into a continuous-tone image. The templates and training images are required in the process of look-up table based methods, which can be obtained from distributed patterns in the sample halftone images and their original images. Although the look-up table based methods usually are faster and show better performances in PSNR than other methods do, they show wide range of qualities depending on how they treat nonexisting patterns in the look-up table. In this paper, a vector adaptive filter is proposed to compensate for these nonexisting patterns, which achieves better quality owing to the contributed informations about hue, saturation, and intensity of surrounding pixels. The experimental results showed that the proposed method resulted in higher PSNR than that of conventional Best Linear Estimation method. The bigger the size of the template in the look-up table becomes, the more outstanding quality in the proposed method can be obtained.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.35.2-42
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• 1999

When we see a binary black and white image, it appears. to our visual sense, to become clearer because of a pseudo halftone. This is because when we don't notice of all the details of the image, instead we see from a more global standpoint. We presented a theory and experimental results for layered model which extended external world, retina and brain of the two dimensional visual model. This paper propose the objective evaluation to coincide with the subjective evaluation of the human in ordered to evaluate the relative merits of the various modulation method. We obtain experimentally the restored images and the measure of approximation of the density four division and ordered dither method. The measure of approximation present s the objective evaluation scale to coincide with the subjective evaluation of the two modulation images.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.06a
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• pp.133-137
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• 2001

본 논문에서는 해프톤 영상의 칼라 분포 특성을 이용하여 해프톤 영상과 비해프톤 영상을 분류하는 방법에 대해 연구하였다. 이를 위해 스캐닝한 RGB 해프톤 영상을 HSV 칼라 모델로 변환한 후, Hue에 대한 히스토그램에서 해프톤 영상이 갖는 고유한 칼라분포 특성을 분석하였다. 일반적으로 해프톤 영상에서는 인쇄시 사용된 칼라들로 인해 특정 Hue 값을 갖는 픽셀의 빈도가 비해프톤 영상과 달리 피크(peak) 형태로 높게 나타나는 특성이 있다. 본 논문에서는 이러한 특성을 고려하여 해프톤 영상과 비해프톤 영상을 구분할 수 있는 분류 방법을 개발하였으며, 실험을 통해 그 타당성을 검토하였다. 제안한 방법은 내용기반 검색시스템에서의 영상분류과정과 문서영상분할 분야 등에서 활용할 수 있다.

• Proceedings of the Korea Multimedia Society Conference
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• 2003.11a
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• pp.144-149
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• 2003

본 논문은 그레이 스케일 인쇄 영상의 저작권을 보호할 수 있는 워터마킹 기법에 관한 연구이다. 기존의 인쇄영상 워터마크 기법은 순서 디더링(ordered dithering)을 이용하는 까닭에 인쇄 영상의 화질 감소가 발생한다. 본 연구에서는 영상 하프토닝 기법중 오류 확산(error diffusion) 알고리즘을 이용하여 화질을 개선한 영상내에 워터마크를 삽입한다. 제안된 알고리즘은 Hagit이 제안한 순서 디더링 셀 집합을 사용한 워터마크를 오류확산 하프토닝 이미지에 삽입함으로 영상의 시각적인 화질 감소가 없을 뿐만 아니라, 프린터와 스캐너에 의한 영상의 변형에도 워터마크의 삽입과 추출이 가능하다. 제안된 알고리즘으로 워터마킹하는 경우 스캐너와 프린터의 기기적인 특성에서 나타나는 잡음과 회전에도 강한 워터마크를 삽입하고 추출할 수 있다.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.85-94
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• 2023

Image halftoning is a technique for varying grayscale images into two-tone binary images. Unfortunately, the static representation of an image-half toning, wherever each pixel intensity is combined by its local neighbors only, causes missing subjective problem. Also, the existing noise causes an instability criterion. In this paper an image half-toning is represented as a dynamical system for recognizing the global representation. Also, noise is reduced based on a probabilistic model. Since image half-toning is considered as 2-D matrix with a full connected pass, this structure is recognized by the dynamical system of Cellular Neural Networks (CNNs) which is defined by its template. Bayesian Rough Sets is used in exploiting the ideal CNNs construction that synthesis its dynamic. Also, Bayesian rough sets contribute to enhance the quality of the halftone image by removing noise and discovering the effective parameters in the CNNs template. The novelty of this method lies in finding a probabilistic based technique to discover the term of CNNs template and define new learning rules for CNNs internal work. A numerical experiment is conducted on image half-toning corrupted by Gaussian noise.