• Title/Summary/Keyword: Bi-level image

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Restoration of Bi-level Images via Iterative Semi-blind Wiener Filtering (반복 semi-blind 위너 필터링을 이용한 이진영상의 복원)

  • Kim, Jeong-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.7
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    • pp.1290-1294
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    • 2008
  • We present a novel deblurring algorithm for bi-level images blurred by some parameterizable point spread function. The proposed method iteratively searches unknown parameters in the point spread function and noise-to-signal ratio by minimizing an objective function that is based on the binariness and the difference between two intensity values of restoring image. In simulations and experiments, the proposed method showed improved performance compared with the Wiener filtering based method in terms of bit error rate after segmentation.

Fast Correction of Nonuniform Illumination on Bi-level Images using Block Based Intensity Normalization (블록 기반 밝기 표준화를 통한 이진영상의 고속 불균일 조명 보정)

  • Joung, Ji-Hye;Kim, Jeong-Tae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.12
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    • pp.1926-1931
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    • 2012
  • We investigated a novel fast non-uniform illumination correction method for bi-level images. The proposed method divides a bi-level image into sub-images and roughly estimates block-wise illumination by low pass filtered maximum values of sub-images. After that, we apply bilinear interpolation using the block-wise illumination to estimate non-uniform illumination, and compensate for the effect of non-uniform illumination using the estimated illumination. Since the proposed method is not based on computation intensive iterative optimization, the proposed method can be used effectively for applications that require fast correction of non-uniform illumination. In simulations, the proposed method showed more than 20 times faster speed than existing entropy minimization method. Moreover, in simulations and experiments, the restored images by the proposed method were more close to true images than images restored by conventional method.

Locally Adaptive Bi-level Image Segmentation Technique (국부 적응 2 진 화상 영역화 기법)

  • Jung, Gyoo-Sung;Park, Rae-Hong
    • Proceedings of the KIEE Conference
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    • 1987.07b
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    • pp.1367-1370
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    • 1987
  • This paper describes a new automatic bi-level image segmentation algorithm which determines local thresholds by applying a locally adaptive edge detection technique to a variable threshold selection method. Computer simulations show that the performance of the proposed algorithm is more robust than those of automatic global thresholding methods.

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Restoration of a Bi-level Waveform by Estimation of Edge Locations (에지 위치 추정을 통한 이진 파형의 복원)

  • Kim, Jeong-Tae
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.55 no.7
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    • pp.327-331
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    • 2006
  • We have proposed an image restoration method for a bi-level waveforms whose number of edges is known to us. Based on the information, we parametrize a bi-level waveform using the locations of edges and restore the waveform by estimating the parameter. We estimated the locations by maximizing the correlation coefficients between the hi-level waveform and the measured waveform. In experiments using two dimensional barcode images of the PDF417 specification, the proposed method showed better performance than conventional methods in the sense that the proposed method was able to decode barcode images that were not decoded by the conventional methods.

Evaluation of Restoration Schemes for Bi-Level Digital Image Degraded by Impulse Noise (임펄스 잡음에 의해 훼손된 이진 디지탈 서류 영상의 복구 방법들의 비교 평가)

  • Shin Hyun-Kyung;Shin Joong-Sang
    • The KIPS Transactions:PartB
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    • v.13B no.4 s.107
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    • pp.369-376
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    • 2006
  • The degradation and its inverse modeling can achieve restoration of corrupted image, caused by scaled digitization and electronic transmission. De-speckle process on the noisy document(or SAR) images is one of the basic examples. Non-linearity of the speckle noise model may hinder the inverse process. In this paper, our study is focused on investigation of the restoration methods for bi-level document image degraded by the impulse noise model. Our study shows that, on bi-level document images, the weighted-median filter and the Lee filter methods are very effective among other spatial filtering methods, but wavelet filter method is ineffective in aspect of processing speed: approximately 100 times slower. Optimal values of the weight to be used in the weighted median filter are investigated and presented in this paper.

Region-Growing Segmentation Algorithm for Rossless Image Compression to High-Resolution Medical Image (영역 성장 분할 기법을 이용한 무손실 영상 압축)

  • 박정선;김길중;전계록
    • Journal of the Institute of Convergence Signal Processing
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    • v.3 no.1
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    • pp.33-40
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    • 2002
  • In this paper, we proposed a lossless compression algorithm of medical images which is essential technique in picture archive and communication system. Mammographic image and magnetic resonance image in among medical images used in this study, proposed a region growing segmentation algorithm for compression of these images. A proposed algorithm was partition by three sub region which error image, discontinuity index map, high order bit data from original image. And generated discontinuity index image data and error image which apply to a region growing algorithm are compressed using JBIG(Joint Bi-level Image experts Group) algorithm that is international hi-level image compression standard and proper image compression technique of gray code digital Images. The proposed lossless compression method resulted in, on the average, lossless compression to about 73.14% with a database of high-resolution digital mammography images. In comparison with direct coding by JBIG, JPEG, and Lempel-Ziv coding methods, the proposed method performed better by 3.7%, 7.9% and 23.6% on the database used.

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Parametric Blind Restoration of Bi-level Images with Unknown Intensities

  • Kim, Daeun;Ahn, Sohyun;Kim, Jeongtae
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.5
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    • pp.319-322
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    • 2016
  • We propose a parametric blind deconvolution method for bi-level images with unknown intensity levels that estimates unknown parameters for point spread functions and images by minimizing a penalized nonlinear least squares objective function based on normalized correlation coefficients and two regularization functions. Unlike conventional methods, the proposed method does not require knowledge about true intensity values. Moreover, the objective function of the proposed method can be effectively minimized, since it has the special structure of nonlinear least squares. We demonstrate the effectiveness of the proposed method through simulations and experiments.

An Edge Profile Adaptive Bi-directional Diffusion Interpolation

  • Kim, Bong-Joe;Sohn, Kwang-Hoon
    • Journal of Broadcast Engineering
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    • v.16 no.3
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    • pp.501-509
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    • 2011
  • In this paper, we propose an edge profile adaptive bi-directional diffusion interpolation method which consists of shock filter and level set. In recent years many interpolation methods have been proposed but all methods have some degrees of artifacts such as blurring and jaggies. To solve these problems, we adaptively apply shock filter and level set method where shock filter enhances edge along the normal direction and level set method removes jaggies artifact along the tangent direction. After the initial interpolation, weights of shock filter and level set are locally adjusted according to the edge profile. By adaptive coupling shock filter with level set method, the proposed method can remove jaggies artifact and enhance the edge. Experimental results show that the average PSNR and MSSIM of our method are increased, and contour smoothness and edge sharpness are also improved.

The Bi-level Image Mapping Using Density Information in Character Patterns (문자패턴에서의 밀도정보를 이용한 이진영상 매핑)

  • 김봉석;강선미;양정윤;양윤모;김덕진
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.8
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    • pp.8-15
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    • 1993
  • This paper describes a normalization of character which is contained in the character recognition process. Line and dot density is computed on input character image and then image mapping is executed into destination. Also recognition is processed using overlap-partitioning of character image and extraction of 4 directional feature primitives. The validity of proposed nonlinear normalization algorithm could be verified by increment of recognition rate.

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A Study on Improved Codeword Extraction for Decoder of Two Dimensional Barcode PDF417 (PDF417 이차원 바코드 디코더에서 코드워드 추출 알고리즘의 성능 개선에 관한 연구)

  • 정정구;한희일
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.89-92
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    • 2002
  • In this paper we present a barcode reader to decode two-dimensional symbology PDF-417 and propose a novel method to extract the bar-space patterns directly from the gray-level barcode image, which employs the location and the distance between extreme points of each row of the barcode image. This algorithm proves to be very robust from the high convolution distortion environments such as defocussing and warping, even under badly illuminating condition. If the scanned barcode image is a result of the convolution of a Gaussian-shaped point spread function with a bi-level image, popular image segmentation methods such as image thresholding can not distinguish between very narrow bar-space patterns with a couple of pixels wide. The proposed algorithm shows improved performance over current barcode readers.

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