• Journal of Korea Multimedia Society
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• v.7 no.3
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• pp.327-339
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• 2004

In this paper, we propose a new watermark algorithm for halftone images using iterative error minimizing method. In the proposed method, watermark bits are hidden at pseudo-random locations within a halftone image. To remove the distortions due to the inserted watermark bits and increase the invisibility of watermark, an iterative error minimizing technique is used. We define the halftoning error is defined as the difference between the original grayscale image and HVS-filtered printed halftone image. Then we iteratively find the pixel pattern with minimum halftoning error and displace the original pixel pattern with it. In order to be robust to geometrical modification like cropping or rotation, we insert the same watermark periodically into halftone images. Experiments using printed and scanned images show that the proposed method is a robust method to the geometrical modification and to hide the large amount of data within a halftone image without noticeable distortion.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.3
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• pp.721-726
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• 2004

The image binarization is applied frequently as one part of the preprocessing phase for a variety of image processing techniques such as character recognition and image analysis, etc. The performance of binarization algorithms is determined by the selection of threshold value for binarization, and most of the previous binarization algorithms analyze the intensity distribution of the original images by using the histogram and determine the threshold value using the mean value of Intensity or the intensity value corresponding to the valley of the histogram. The previous algorithms could not get the proper threshold value in the case that doesn't show the bimodal characteristic in the intensity histogram or for the case that tries to separate the feature area from the original image. So, this paper proposed the novel algorithm for image binarization, which, first, segments the intensity range of grayscale images to several intervals and calculates mean value of intensity for each interval, and next, repeats the interval integration until getting the final threshold value. The interval integration of two neighborhood intervals calculates the ratio of the distances between mean value and adjacent boundary value of two intervals and determine as the threshold value of the new integrated interval the intensity value that divides the distance between mean values of two intervals according to the ratio. The experiment for performance evaluation of the proposed binarization algorithm showed that the proposed algorithm generates the more effective threshold value than the previous algorithms.

• Proceedings of the Korean Information Science Society Conference
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• 2004.10b
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• pp.754-756
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• 2004

본 논문에서는 흑백 및 칼라 카메라를 동시에 이용한 사용자 컬러 영상 추출에 대하여 소개한다. 영상으로부터 사용자를 추출하기 위해 일반적으로 이용되는 방법은 배경이 정적이고 조명 조건이 일정하다는 전제를 가정한다. 따라서 프로젝션 기반 가상환경과 같이 어둡고 스크린으로 투사되는 빛으로 인해 조명 조건이 계속 변하는 환경에서는 이러한 방법들을 적용하기 어렵다. 제안하는 방법에서는 적외선 반사 영상(infrared reflective image)을 사용하여 사용자 영역을 강건하게 정의할 수 있으며, 정의된 사용자 영역에 대한 컬러 값을 제공하기 위하여 별도의 칼라 카메라를 설치하여 두 영상을 매핑한다. 이 방법은 CAVE$^{TM}$-like 시스템과 같은 환경에도 적용될 수 있기 때문에 가상협업환경에서의 텔레프레센스를 제공하기 위해서도 효과적으로 사용될 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.4
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• pp.840-855
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• 2011

In the context of additive noise steganography model, we propose a method to detect least significant bit (LSB) matching steganography in grayscale images. Images are decomposed into detail sub-bands with local linear transform (LLT) masks which are sensitive to embedding. Novel normalized characteristic function features weighted by a bank of band-pass filters are extracted from the detail sub-bands. A suboptimal feature set is searched by using a threshold selection algorithm. Extensive experiments are performed on four diverse uncompressed image databases. In comparison with other well-known feature sets, the proposed feature set performs the best under most circumstances.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.1
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• pp.35-41
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• 2003

In this paper, a machine vision system for recognizing and classifying the patterns and marks engraved by die molding or laser marking on the glass panels of computer monitors is suggested and evaluated experimentally. The vision system is equipped with a neural network and an NGC pattern classifier including searching process based on normalized grayscale correlation and adaptive binarization. This system is found to be applicable even to the cases in which the segmentation of the pattern area from the background using ordinary blob coloring technique is quite difficult. The inspection process is accomplished by the use of the NGC hypothesis and ANN verification. The proposed pattern recognition system is composed of three parts: NGC matching process and the preprocessing unit for acquiring the best quality of binary image data, a neural network-based recognition algorithm, and the learning algorithm for the neural network. Another contribution of this paper is the method of generating the training patterns from only a few typical product samples in place of real images of all types of good products.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.373-376
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• 2013

Nowadays, eyes detection is required and considered as the most important step in several applications, such as eye tracking, face identification and recognition, facial expression analysis and iris detection. This paper presents the eyes detection in facial images using Harris corner detection. Firstly, Haar-like features for face detection is used to detect a face region in an image. To separate the region of the eyes from a whole face region, the projection function is applied in this paper. At the last step, Harris corner detection is used to detect the eyes location. In experimental results, the eyes location on both grayscale and color facial images were detected accurately and effectively.

• 한국정보디스플레이학회:학술대회논문집
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• 2005.07a
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• pp.276-279
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• 2005

The proposed Novel OverDriving Technology with Optimum Look-up-Table（LUT）is suggested to be a better solution to reducing the occurrence of overshooting caused by the traditional overdriving method implemented to normally liquid crystal (VA mode). Chunghwa Picture Tubes, LTD. (CPT) has successfully implement this tech into 20 inch TFTLCD TV module at the present day. The proposed technology can speed up gray-to-gray response time of LCD less than one half of frame time. On the side, Optimum LUT construction apply the compression scheme to record total actual grayscale transfer characteristics instead of applying the normal spread method such as linear / non-linear interpolation. The memory space is been reduced and the distortion of the image quality is lesser.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05b
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• pp.595-598
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• 2004

In this paper, a shape decomposition method using morphological operations is studied for decomposing the complex shape in 2-D mage into its simple primitive elements. The serious drawback of conventional shape representation algorithm is that the primitive elements are extracted too much to represent the shape and the processing time is long. To solve these problems, a new shape decomposition algorithm using the 8 bit planes obtained from gray code is proposed.

• International journal of advanced smart convergence
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• v.10 no.2
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• pp.45-52
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• 2021

The surveillance camera market has developed and plays an important role in the field of video surveillance. However, in recent years, the identification of areas requiring surveillance has been limited by reflective light in the surveillance camera market. Cameras using polarization filters are being developed to reduce reflective light and facilitate identification. Programs are required to automatically adjust polarization filters. In this paper, we proposed an optimal angle extraction method from surveillance cameras using polarization filters through histogram analysis. First of all, transformed to grayscale to analyze the specifications of frames in multiple polarized angle images, reducing computational throughput. Then we generated and analyzed a histogram of the corresponding frame to extract the angle when the highlights are the fewest. Experiments with 0˚ and 90˚ showed high performance in extracting optimal angles. At this point, it is hoped this technology would be used for surveillance cameras in place like beach with a lot of reflective light.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.589-601
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• 2014

The performance of edge detection often relies on its ability to correctly determine the dissimilarities of connected pixels. For grayscale images, the dissimilarity of two pixels is estimated by a scalar difference of their intensities and for color images, this is done by using the vector difference (color distance) of the three-color components. The Euclidean distance in the RGB color space typically measures a color distance. However, the RGB space is not suitable for edge detection since its color components do not coincide with the information human perception uses to separate objects from backgrounds. In this paper, we propose a novel method for color edge detection by taking advantage of the HSV color space and the Mahalanobis distance. The HSV space models colors in a manner similar to human perception. The Mahalanobis distance independently considers the hue, saturation, and lightness and gives them different degrees of contribution for the measurement of color distances. Therefore, our method is robust against the change of lightness as compared to previous approaches. Furthermore, we will introduce a noise-resistant technique for determining image gradients. Various experiments on simulated and real-world images show that our approach outperforms several existing methods, especially when the images vary in lightness or are corrupted by noise.