• Smart Media Journal
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• v.4 no.4
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• pp.9-17
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• 2015

Recently the need for advanced security technologies are increasing as the occurrence of intelligent crime is growing fastly. Previous liveness detection and fake face detection methods are required for the improvement of accuracy in order to be put to practical use. In this paper, we propose a new liveness detection method using pupil reflection, and new fake image detection using Adaboost detector. The proposed system detects eyes based on multi-scale Gabor feature vector in the first stage, The template matching plays a role in determining the allowed eye area. And then, the reflected image in the pupil is used to decide whether or not the captured image is live or not. Experimental results indicate that the proposed method is superior to the previous methods in the detection accuracy of fake images.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.252-257
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• 2007

우리나라의 항만은 수 출입화물의 99.5%를 처리하며, 육로 및 철도 수송 물동량의 기종점 역할을 수행하는 중요한 곳으로서 항만 물동량의 신속한 처리와 자동화 시스템에 의한 비용절감은 엄청난 효과를 가져온다. 따라서 본 논문에서는 항만에서 취급하는 컨테이너를 자동으로 식별할 수 있는 자동화 방법을 제안한다. 실제 컨테이너 영상을 그레이 영상으로 변환한 후, 프리윗 마스크(Prewitt-Mask)를 적용하여 윤곽선을 추출하고 컨테이너를 식별할 수 있는 개별 식별자의 형태학적 특징 정보를 이용하여 식별자 후보영역을 검출한다. 검출된 식별자 후보영역은 개별 식별자 영역외에 잡음 영역이 포함되어 있으므로 4방향 윤곽선 추적 알고리즘과 Grassfire 알고리즘을 적용하여 잡음을 제거하고 개별 식별자들을 각각 객체화한다. 잡음이 제거된 식별자 후보 영역에서 객체화 한 개별 식별자는 컨테이너 식별을 위해 FCM 기반 퍼지 RBF 네트워크를 적용하여 인식한다. 본 논문에서 제안한 컨테이너 식별자 인식 방법의 성능을 평가하기 위해 실제 컨테이너 영상 300장을 대상으로 실험한 결과, 기존의 방법보다 인식 성능이 개선되었음을 확인할 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.666-668
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• 2016

Salt and pepper noise generally occurs due to errors in the transmission channel or sensors and it lowers the resolution of the image and causes visual errors. To remove this salt and pepper noise, SMF(standard median filter), which represents simple algorithm and excellent noise removal performance, is widely used. However preservation characteristics in the pitch areas of the image is rather lacking. Therefore to effectively restore images damaged by salt and pepper noise, the study suggested a multiple filter that applies filters differently according to size by applying noise density threshold value of local mask on noise signal, while preserving non-noise signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.3
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• pp.735-741
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• 2014

Edge in images appears when a great difference shows up in light and shade between pixels and includes data of the subject's size, location direction and etc. The edge is generally detected by the methods such as Sobel, Roberts, Laplacian, LoG(Laplacian of Gaussian) and etc. However, in AWGN(additive white Gaussian noise) added images, quality of the edge becomes slightly uncertain. Therefore, this paper proposed edge detection algorithm using modified mask of weighting to improve the quality of the existing methods. And in order to verify the performance efficiency of the proposed method, processed image and PFOM(Pratt's figure of merit) has been used as valuation standard for a comparison with the existing methods.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.353-361
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• 2012

In this paper, we propose a improvement method of vision inspector for T type welding nut using an auto sorting system. We used edge and thread detection with histogram of image which is captured by machine vision camera. We also used a binary morphology operation for a detection of spot. A major problem in this vision inspector is abnormal operation caused by degradation of image acquired. These degradations caused by oil pollution on conveyer belt. For overcome this problem, we introduce a pre-processing using a masked histogram equalization on the image acquired. Histogram equalization is applied on masked region (nut part) for increase contrast. As a result, we can remove features caused by oil pollution on background and reduce a ratio of abnormal operation from 10.0 % to 0.2 %.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1479-1486
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• 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
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• v.20 no.3
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• pp.647-653
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• 2016

Recently, the data image processing has been applied to a variety of fields including broadcasting, communication, computer graphics, medicine, and so on. Generally, the image data may develop the noise during their transmission. Therefore, the studies have been actively conducted to remove the noise on the image. There are diverse types of noise on the image including salt and pepper noise, AWGN, and mixed noise. Hence, the filter algorithm for the image recovery was proposed that salt and pepper noise was processed by histogram and spatial weighted values after defining the noise to lessen the impact of mixed noise added in the image, and AWGN was processed by the pixel information of local mask establishing the weighted values in this study. Regarding the processed results by applying Lena images which were corrupted by salt and pepper noise(P=50%) and AWGN(${\sigma}=10$), suggested algorithm showed the improvement by 7.06[dB], 10.90[dB], 5.97[dB] respectively compared with the existing CWMF, A-TMF, AWMF.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.130-136
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• 2017

Recently, as demand of video processor unit rapidly increases, excellent quality of the video has been required. However, generally, video data occurs the quick flame of video due to various external causes in process of acquisition, treatment, and transmission, and major cause of the quick flame of the video is known as the noise. There are various kinds of noise, which are added to the video, AWGN is a typical one. Thus, this thesis suggested algorithm that treats in three methods by scale of the edge through using edge information of local masks. In case that edge pixel is big, it applied spatial weighting according to equation of straight line about direction of edge pixel. In case that edge pixel is middle, it suggested algorithm with spatial weighting filter and average filter, and for the smooth territory, it suggested algorithm that treats with average filter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.6
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• pp.867-873
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• 2018

Recently, interests in the field of image processing have increased with the increased demand for digital imaging devices. However, digital images are damaged by the noise generated by various causes during image processing. Generally in digital imaging devices, noise such as AWGN, etc. is generated and performance and reliability are deteriorated, and various researches are in progress to remove it. Accordingly in the present paper, an algorithm to protect the high frequency components of the images and to efficiently remove AWGN is proposed. The proposed algorithm calculates the final output by adjusting estimate values applied with Gaussian mask and weight values applied according to the local mask distribution. And for performance evaluation of the proposed algorithm, simulations were performed with the existing methods, and the characteristics were compared through PSNR and the processed, enlarged images.

• Journal of KIISE:Software and Applications
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• v.32 no.2
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• pp.128-139
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• 2005

Moving object boundary is very important for moving object segmentation. But the moving object boundary shows broken boundary We invent a novel space-oriented boundary linking algorithm to link the broken boundary The boundary linking algorithm forms a quadrant around the terminating pixel in the broken boundary and searches forward other terminating pixel to link within a radius. The boundary linking algorithm guarantees shortest distance linking. We also register the background from image sequence. We construct two object masks, one from the result of boundary linking and the other from the registered background, and use these two complementary object masks together for moving object segmentation. We also suppress the moving cast shadow using Roberts gradient operator. The major advantages of the proposed algorithms are more accurate moving object segmentation and the segmentation of the object which has holes in its region using these two object masks. We experiment the algorithms using the standard MPEG-4 test sequences and real video sequence. The proposed algorithms are very efficient and can process QCIF image more than 48 fps and CIF image more than 19 fps using a 2.0GHz Pentium-4 computer.