• Title/Summary/Keyword: Separating image

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Automated radiation field edge detection in portal image using optimal threshold value (최적 문턱치 설정을 이용한 포탈영상에서의 자동 에지탐지 기법에 관한 연구)

  • 허수진
    • Journal of Biomedical Engineering Research
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    • v.16 no.3
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    • pp.337-344
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    • 1995
  • Because of the high energy of the treatment beam, contrast of portal films is very poor. Many image processing techniques have been applied to the portal images but a significant drawback is the loss of definition on the edges of the treatment field. Analysis of this problem shows that it may be remedied by separating the treatment field from the background prior to enhancement and uslng only the pixels within the field boundary in the enhancement procedure. A new edge extraction algorithm for accurate extraction of the radiation field boundary from portal Images has been developed for contrast enhancement of portal images. In this paper, portal image segmentation algorithm based on Sobel filtration, labelling processes and morphological thinning has been presented. This algorithm could automatically search the optimal threshold value which is sensitive to the variation of the type and quality of portal images.

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Machine Learning Based Automatic Categorization Model for Text Lines in Invoice Documents

  • Shin, Hyun-Kyung
    • Journal of Korea Multimedia Society
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    • v.13 no.12
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    • pp.1786-1797
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    • 2010
  • Automatic understanding of contents in document image is a very hard problem due to involvement with mathematically challenging problems originated mainly from the over-determined system induced by document segmentation process. In both academic and industrial areas, there have been incessant and various efforts to improve core parts of content retrieval technologies by the means of separating out segmentation related issues using semi-structured document, e.g., invoice,. In this paper we proposed classification models for text lines on invoice document in which text lines were clustered into the five categories in accordance with their contents: purchase order header, invoice header, summary header, surcharge header, purchase items. Our investigation was concentrated on the performance of machine learning based models in aspect of linear-discriminant-analysis (LDA) and non-LDA (logic based). In the group of LDA, na$\"{\i}$ve baysian, k-nearest neighbor, and SVM were used, in the group of non LDA, decision tree, random forest, and boost were used. We described the details of feature vector construction and the selection processes of the model and the parameter including training and validation. We also presented the experimental results of comparison on training/classification error levels for the models employed.

Polar-Format-Processing-Based Moving Target Imaging in MIMO Radar Environment (MIMO 레이다 환경에서 Polar Format Processing 기반 이동표적 이미징)

  • Choi, Sang-Hyun;Yang, Hoon-Gee
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.30 no.2
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    • pp.124-131
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    • 2019
  • This study presents an imaging algorithm that can provide an image of a moving target in a multiple-input-multiple-output radar environment where multiple transmitting and receiving radars are fixed on the ground. The proposed algorithm, which is based on polar format processing using plane wave approximation, is shown to provide an unaliased image by using multiple transmitting radars even when the distances between the receiving radars are relatively large. We derive the conditions necessary to deploy the transmitting radars by which the resolution of the reconstructed image can be improved, while simultaneously reducing aliasing artifacts. Moreover, we offer a means of separating out each transmitting radar target echo. Finally, the performance of the proposed system is verified through a simulation.

An Effective Method of Product Number Detection from Thick Plates (효과적인 후판의 제품번호 검출 방법)

  • Park, Sang-Hyun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.10 no.1
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    • pp.139-148
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    • 2015
  • In this paper, a new algorithm is proposed for detecting the product number of each thick plate and extracting each character of the product number from a image which contains several thick plates. In general, a image of thick plates contains several steal plates. To obtain the product number from the image, we first need to separate each plate. To do so, we use the line edges of thick plates and a clustering algorithm. After separating each plate, background parts are eliminated from the image of each plate. Background parts of an individual thick plate image consist of the dark part of steel and the white part of paint which is used for printing the product number. We propose a two-tiered method where dark background parts are first eliminated and then white parts are eliminated. Finally, each character is extracted from the product number image using the characteristics of product number. The results of the experiments on the various steal plates images emphasize that the proposed algorithm detects each thick plate and extracts the product number from a image effectively.

Character Segmentation and Recognition Algorithm for Various Text Region Images (다양한 문자열영상의 개별문자분리 및 인식 알고리즘)

  • Koo, Keun-Hwi;Choi, Sung-Hoo;Yun, Jong-Pil;Choi, Jong-Hyun;Kim, Sang-Woo
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.58 no.4
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    • pp.806-816
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    • 2009
  • Character recognition system consists of four step; text localization, text segmentation, character segmentation, and recognition. The character segmentation is very important and difficult because of noise, illumination, and so on. For high recognition rates of the system, it is necessary to take good performance of character segmentation algorithm. Many algorithms for character segmentation have been developed up to now, and many people have been recently making researches in segmentation of touching or overlapping character. Most of algorithms cannot apply to the text regions of management number marked on the slab in steel image, because the text regions are irregular such as touching character by strong illumination and by trouble of nozzle in marking machine, and loss of character. It is difficult to gain high success rate in various cases. This paper describes a new algorithm of character segmentation to recognize slab management number marked on the slab in the steel image. It is very important that pre-processing step is to convert gray image to binary image without loss of character and touching character. In this binary image, non-touching characters are simply separated by using vertical projection profile. For separating touching characters, after we use combined profile to find candidate points of boundary, decide real character boundary by using method based on recognition. In recognition step, we remove noise of character images, then recognize respective character images. In this paper, the proposed algorithm is effective for character segmentation and recognition of various text regions on the slab in steel image.

Panorama Background Generation and Object Tracking using Pan-Tilt-Zoom Camera (Pan-Tilt-Zoom 카메라를 이용한 파노라마 배경 생성과 객체 추적)

  • Paek, In-Ho;Im, Jae-Hyun;Park, Kyoung-Ju;Paik, Jun-Ki
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.3
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    • pp.55-63
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    • 2008
  • This paper presents a panorama background generation and object tracking technique using a Pan-Tilt-Zoom camera. The proposed method estimates local motion vectors rapidly using phase correlation matching at the prespecified multiple local regions, and it makes minimized estimation error by vector quantization. We obtain the required image patches, by estimating the overlapped region using local motion vectors, we can then project the images to cylinder and realign the images to make the panoramic image. The object tracking is performed by extracting object's motion and by separating foreground from input image using background subtraction. The proposed PTZ-based object tracking method can efficiently generated a stable panorama background, which covers up to 360 degree FOV The proposed algorithm is designed for real-time implementation and it can be applied to many commercial applications such as object shape detection and face recognition in various surveillance video systems.

An effective classification method for TFT-LCD film defect images using intensity distribution and shape analysis (명암도 분포 및 형태 분석을 이용한 효과적인 TFT-LCD 필름 결함 영상 분류 기법)

  • Noh, Chung-Ho;Lee, Seok-Lyong;Zo, Moon-Shin
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1115-1127
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    • 2010
  • In order to increase the productivity in manufacturing TFT-LCD(thin film transistor-liquid crystal display), it is essential to classify defects that occur during the production and make an appropriate decision on whether the product with defects is scrapped or not. The decision mainly depends on classifying the defects accurately. In this paper, we present an effective classification method for film defects acquired in the panel production line by analyzing the intensity distribution and shape feature of the defects. We first generate a binary image for each defect by separating defect regions from background (non-defect) regions. Then, we extract various features from the defect regions such as the linearity of the defect, the intensity distribution, and the shape characteristics considering intensity, and construct a referential image database that stores those feature values. Finally, we determine the type of a defect by matching a defect image with a referential image in the database through the matching cost function between the two images. To verify the effectiveness of our method, we conducted a classification experiment using defect images acquired from real TFT-LCD production lines. Experimental results show that our method has achieved highly effective classification enough to be used in the production line.

An Approach of Hiding Hangul Secret Message in Image using XNOR-XOR and Fibonacci Technique (XNOR-XOR과 피보나치 기법을 이용하여 이미지에서 한글 비밀 메시 지를 은닉하는 방법)

  • Ji, Seon-su
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.14 no.2
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    • pp.109-114
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    • 2021
  • As various users increase in a network environment, it is difficult to protect sensitive and confidential information transmitted and received from attackers. Concealing bitwise secret data in an image using the LSB technique can be very vulnerable to attack. To solve this problem, a hybrid method that combines encryption and information hiding is used. Therefore, an effective method for users to securely protect secret messages and implement secret communication is required. A new approach is needed to improve security and imperceptibility to ensure image quality. In this paper, I propose an LSB steganography technique that hides Hangul messages in a cover image based on MSB and LSB. At this time, after separating Hangul into chosung, jungsung and jongsung, the secret message is applied with Exclusive-OR or Exclusive-NOR operation depending on the selected MSB. In addition, the calculated secret data is hidden in the LSB n bits of the cover image converted by Fibonacci technique. PSNR was used to confirm the effectiveness of the applied results. It was confirmed 41.517(dB) which is suitable as an acceptable result.

Adaptive Optimal Thresholding for the Segmentation of Individual Tooth from CT Images (CT영상에서 개별 치아 분리를 위한 적응 최적 임계화 방안)

  • Heo, Hoon;Chae, Ok-Sam
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.3
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    • pp.163-174
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    • 2004
  • The 3D tooth model in which each tooth can be manipulated individualy is essential component for the orthodontic simulation and implant simulation in dental field. For the reconstruction of such a tooth model, we need an image segmentation algorithm capable of separating individual tooth from neighboring teeth and alveolar bone. In this paper we propose a CT image normalization method and adaptive optimal thresholding algorithm for the segmenation of tooth region in CT image slices. The proposed segmentation algorithm is based on the fact that the shape and intensity of tooth change gradually among CT image slices. It generates temporary boundary of a tooth by using the threshold value estimated in the previous imge slice, and compute histograms for the inner region and the outer region seperated by the temporary boundary. The optimal threshold value generating the finnal tooth region is computed based on these two histogram.

Color Transfer Method Based on Separation of Saturation (채색 분리 기반의 색 변환 기법)

  • Kwak, Jung-Min;Kim, Jae-Hyup;Moon, Young-Shik
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.45 no.3
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    • pp.149-159
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    • 2008
  • We present new methods which transfer the color style of a source image into an arbitrary given reference image. Misidentification problem of color cause wrong indexing in low saturation. Therefore, the proposed method do indexing after Image separating chromatic and achromatic color from saturation. The proposed method is composed of the following four steps : In the first step, Image separate chromatic and achromatic color from saturation using threshold. In the second step, image of separation do indexing using cylindrical metric. In the third step, the number and positional dispersion of pixel decide the order of priority for each index color. And average and standard deviation of each index color be calculated. In the final step, color be transferred in Lab color space, and post processing to removal noise and pseudo-contour. Experimental results show that the proposed method is effective on indexing and color transfer.