• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2002년도 하계종합학술대회 논문집(4)
• /
• pp.161-164
• /
• 2002

We propose a new method for rotational image retrieval that it is based on highly related property between a spatial image and wavelet transform. The characteristics have an important role in the design of our algorithm. Our proposed algorithm for rotational image retrieval is to obtain same image or rotated image. Because our algorithm used an rotational image retrieval.

• 한국정보전자통신기술학회논문지
• /
• 제10권6호
• /
• pp.617-625
• /
• 2017

본 논문에서는 기밀 데이터를 커버 이미지에 은닉하는 효과적인 가역 데이터 은닉 기법을 제안하였다. 제안된 기법에서는 이미지에 존재하는 지역적 유사성을 이용하여 픽셀 값을 정확하게 예측하여 예측 이미지를 생성하였고, 생성된 예측 이미지와 원본 커버 이미지를 사용하여 차분 시퀀스를 생성한 후, 히스토그램 쉬프트 기법을 적용하여 기밀데이터가 은닉된 스테고 이미지(stego-image)를 생성하였다. 스테고 이미지로부터 기밀 데이터를 추출하고 원본 커버 이미지를 손실 없이 복원할 수 있다. 제안된 기법을 적용하면 기존의 APD 기법에 비하여 더 많은 기밀 데이터를 은닉할 수 있음을 실험으로 확인하였다.

• Communications for Statistical Applications and Methods
• /
• 제29권2호
• /
• pp.277-286
• /
• 2022

Due to the uniquely slow convergence speed of the EM algorithm, it suffers form a lot of processing time until the desired deconvolution image is obtained when the image is large. To cope with the problem, in this paper, an immediate solution of the EM algorithm is provided under the Gaussian image model. It is derived by finding the recurrent formular of the EM algorithm and then substituting the results repeatedly. In this paper, two types of immediate soultion of image deconboution by EM algorithm are provided, and both methods have been shown to work well. It is expected that it free the processing time of image deconvolution because it no longer requires an iterative process. Based on this, we can find the statistical properties of the restored image at specific iterates. We demonstrate the effectiveness of the proposed method through a simple experiment, and discuss future concerns.

• 한국공작기계학회:학술대회논문집
• /
• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
• /
• pp.115-120
• /
• 2000

This study is on the application the image processing algorithm for inspection of the aluminium mill strip surface defect. The image of surface defect data was obtained using the CCD camera with the digital signal board. The edge was found from the difference of pixel intensity between the normal image and defect image. Two step were taken to find the edge in the image processing algorithm. First, noise was removed by using the median filter in the image. Second, the edge was sharpened in detail by using the sharpening convolution filter in the image. Canny algorithm was used to defect the exact edge. The defect section was separated from the original image is to find the coordination point p1 and p2 which include the defect image

• 한국컴퓨터정보학회논문지
• /
• 제21권8호
• /
• pp.1-12
• /
• 2016

In this paper, we propose a very efficient reversible data hiding algorithm using spatial locality and the surface characteristics of image. Spacial locality and a variety of surface characteristics are present in natural images. So, it is possible to precisely predict the pixel value using the locality and surface characteristics of image. Therefore, the frequency is increased significantly at the peak point of the difference histogram using the precisely predicted pixel values. Thus, it is possible to increase the amount of data to be embedded in image using the spatial locality and surface characteristics of image. By using the proposed reversible data hiding algorithm, visually high quality stego-image can be generated, the embedded data and the original cover image can be extracted without distortion from the stego-image, and the embedding data are much greater than that of the previous algorithm. The experimental results show the superiority of the proposed algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제8권8호
• /
• pp.2881-2894
• /
• 2014

In complicated environment, context information plays an important role in image segmentation/labeling. The recently proposed auto-context algorithm is one of the effective context-based methods. However, the standard auto-context approach samples the context locations utilizing a fixed radius sequence, which is sensitive to large scale-change of objects. In this paper, we present a scale invariant auto-context (SIAC) algorithm which is an improved version of the auto-context algorithm. In order to achieve scale-invariance, we try to approximate the optimal scale for the image in an iterative way and adopt the corresponding optimal radius sequence for context location sampling, both in training and testing. In each iteration of the proposed SIAC algorithm, we use the current classification map to estimate the image scale, and the corresponding radius sequence is then used for choosing context locations. The algorithm iteratively updates the classification maps, as well as the image scales, until convergence. We demonstrate the SIAC algorithm on several image segmentation/labeling tasks. The results demonstrate improvement over the standard auto-context algorithm when large scale-change of objects exists.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
• /
• pp.167-170
• /
• 2000

In this paper, we propose the edge compensation algorithm which connects the adjacent edges without losing the information of the skeletons on the edge image. The proposed edge compensation algorithm is composed of succeeding two steps. In the first step, the uplifted image is obtained by applying the uplifting process to the edge image. The next step is to extract the edge image from the uplifted image using the skeleton extraction algorithm. Experimental results show that the proposed method connects the adjacent edges without the distortion of the original edge information compared to the traditional method

• 한국멀티미디어학회논문지
• /
• 제21권3호
• /
• pp.342-347
• /
• 2018

We proposed a fast detection of copy-move image forgery using four step search algorithm in the spatial domain. In the four-step search algorithm, the search area is 21 (-10 ~ +10), and the number of pixels to be scanned is 33. Our algorithm reduced computational complexity more than conventional copy move image forgery methods. The proposed method reduced 92.34 % of computational complexity compare to exhaustive search algorithm.

• 제어로봇시스템학회논문지
• /
• 제17권2호
• /
• pp.145-148
• /
• 2011

In this paper, we proposed a search method for structured light pixels of omnidirectional structured light image. Since the omnidirectional structured light image is composed of several circular arc segments, the proposed algorithm searches the structured light pixels in radial direction rather than horizontal or vertical directions. The proposed search algorithm is based on the well-known Bresenham raster algorithm for line drawing in discrete integer space, thereby computation of the algorithm is very efficient. Comparison results between the proposed search algorithm and the conventional horizontal search are presented in experiments.

• Nuclear Engineering and Technology
• /
• 제51권3호
• /
• pp.719-722
• /
• 2019

Gamma-ray images generally suffer from a lot of noise because of low photon detection in the gamma camera system. The purpose of this study is to improve the image quality in gamma-ray images using a gamma camera system with a fast nonlocal means (FNLM) noise reduction algorithm with an acceleration function. The designed FNLM algorithm is based on local region considerations, including the Euclidean distance in the gamma-ray image and use of the encoded information. To evaluate the noise characteristics, the normalized noise power spectrum (NNPS), contrast-to-noise ratio (CNR), and coefficient of variation (COV) were used. According to the NNPS result, the lowest values can be obtained using the FNLM noise reduction algorithm. In addition, when the conventional methods and the FNLM noise reduction algorithm were compared, the average CNR and COV using the proposed algorithm were approximately 2.23 and 7.95 times better than those of the noisy image, respectively. In particular, the image-processing time of the FNLM noise reduction algorithm can achieve the fastest time compared with conventional noise reduction methods. The results of the image qualities related to noise characteristics demonstrated the superiority of the proposed FNLM noise reduction algorithm in a gamma camera system.