• Title/Summary/Keyword: 블록영역분류

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System Implementation of Paper Currency Discrimination by Using Integrated Image Features (통합 영상 특징에 의한 지폐 분류 시스템의 구현)

  • Gang, Hyeon-In;Choe, Tae-Wan
    • The KIPS Transactions:PartB
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    • v.9B no.4
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    • pp.471-480
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    • 2002
  • In this paper, we implemented a real-time system improving the performance of the paper currency discrimination by integrating a weighted region of interest matching algorithm with a weighted shape feature matching algorithm of the blocked image. The system classifies the paper currency by comparing a query image with compared images based on the database that contain images of paper currency. Especially, the system has good efficiency at the contaminated, rotated, and translated paper currency. The system hardware consists of three parts as follows : the paper currency image acquired by CIS(contact image sensor) is applied to the pre-processing part with A/D converter and PLD. Finally the pre-processed image data are classified by the main image processing part with a high-speed DSP based on the proposed algorithm.

Image Compression using Validity and Zero Coefficients by DCT(Discrete Cosine Transform) (DCT에서 유효계수와 Zero계수를 이용한 영상 압축)

  • Kim, Jang Won;Han, Sang Soo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.1 no.3
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    • pp.97-103
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    • 2008
  • In this paper, $256{\times}256$ input image is classified into a validity block and an edge block of $8{\times}8$ block for image compression. DCT(Discrete Cosine Transform) is executed only for the DC coefficient that is validity coefficients for a validity block. Predict the position where a quantization coefficient becomes 0 for an edge block, I propose new algorithm to execute DCT in the reduced region. Not only this algorithm that I proposed reduces computational complexity of FDCT(Forward DCT) and IDCT(Inverse DCT) and decreases encoding time and decoding time. I let compressibility increase by accomplishing other stability verticality zigzag scan by the block size that was classified for each block at the time of huffman encoding each. In addition, the algorithm that I suggested reduces Run-Length by accomplishing the level verticality zigzag scan that is good for a classified block characteristic and, I offer the compressibility that improved thereby.

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Fast Multiresolution Motion Estimation in Wavelet Transform Domain Using Block Classification and HPAME (블록 분류와 반화소 단위 움직임 추정을 이용한 웨이브릿 변환 영역에서의 계층적 고속 움직임 추정 방법)

  • Gwon, Seong-Geun;Lee, Seok-Hwan;Ban, Seung-Won;Lee, Geon-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.39 no.2
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    • pp.87-95
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    • 2002
  • In this paper, we proposed a fast multi-resolution motion estimation(MRME) algorithm. This algorithm exploits the half-pixel accuracy motion estimation(HPAME) for exact motion vectors in the baseband and block classification for the reduction of bit amounts and computational loads. Generally, as the motion vector in the baseband are used as initial motion vector in the high frequency subbands, it has crucial effect on quality of the motion compensated image. For this reason, we exploit HPAME in the motion estimation for the baseband. But HPAME requires additional bit and computational loads so that we use block classification for the selective motion estimation in the high frequency subbands to compensate these problems. In result, we could reduce the bit rate and computational load at the similar image quality with conventional MRME. The superiority of the proposed algorithm was confirmed by the computer simulation.

Preliminary Estimation of Earthquake Losses Based on HAZUS in a Coastal Facility Area with Blocks Applying Site Classification (블록별 부지분류 적용 해안시설 영역에서의 HAZUS 기반 지진피해 추정)

  • Sun, Chang-Guk;Chun, Sung-Ho
    • Journal of the Korean Association of Geographic Information Studies
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    • v.17 no.4
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    • pp.10-27
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    • 2014
  • HAZUS-MH is a GIS-based computer program that estimates potential losses from multi-hazard phenomena: earthquakes, floods and hurricanes. With respect to seismic disaster, characteristics of a hypothetical or actual earthquake are entered into HAZUS. Then HAZUS estimates the intensity of ground shaking and calculates the correspondent losses. In this study, HAZUS was used as a part of the preparations of the future seismic events at a coastal plant facility area. To reliably characterize the target facility area, many geotechnical characteristics data were synthesized from the existing site investigation reports. And the buildings and facilities were sorted by analyzing their material and structural characteristics. In particular, the study area was divided into 17 blocks taking into account the situation of both land development and facility distribution. The ground conditions of blocks were categorized according to the site classification scheme for earthquake-resistant design. Moreover, seismic fragility curves of a main facilities were derived based on the numerical modeling and were incorporated into the database in HAZUS. The results estimated in the study area using HAZUS showed various seismic damage and loss potentials depending on site conditions and structural categories. This case study verified the usefulness of the HAZUS for estimating earthquake losses in coastal facility areas.

Bar Code Location Algorithm Using Pixel Gradient and Labeling (화소의 기울기와 레이블링을 이용한 효율적인 바코드 검출 알고리즘)

  • Kim, Seung-Jin;Jung, Yoon-Su;Kim, Bong-Seok;Won, Jong-Un;Won, Chul-Ho;Cho, Jin-Ho;Lee, Kuhn-Il
    • The KIPS Transactions:PartD
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    • v.10D no.7
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    • pp.1171-1176
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    • 2003
  • In this paper, we propose an effective bar code detection algorithm using the feature analysis and the labeling. After computing the direction of pixels using four line operators, we obtain the histogram about the direction of pixels by a block unit. We calculate the difference between the maximum value and the minimum value of the histogram and consider the block that have the largest difference value as the block of the bar code region. We get the line passing by the bar code region with the selected block but detect blocks of interest to get the more accurate line. The largest difference value is used to decide the threshold value to obtain the binary image. After obtaining a binary image, we do the labeling about the binary image. Therefore, we find blocks of interest in the bar code region. We calculate the gradient and the center of the bar code with blocks of interest, and then get the line passing by the bar code and detect the bar code. As we obtain the gray level of the line passing by the bar code, we grasp the information of the bar code.

Image Segmentation Using Block Classification and Watershed Algorithm (블록분류와 워터쉐드를 이용한 영상분할 알고리듬)

  • Lim, Jae-Hyuck;Park, Dong-Kwon;Won, Chee-Sun
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.36S no.1
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    • pp.81-92
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    • 1999
  • In this paper, we propose a new image segmentation algorithm which can be use din object-based image coding applications such as MPGA-4. Since the conventional objet segmentation methods based on mathematical morphology tend to yield oversegmented results, they normally need a postprocess which merges small regions to obtain a larger one. To solve this oversegmentation problem, in this paper, we prosed a block-based segmentation algorithm that can identify large texture regions in the image. Also, by applying the watershed algorithm to the image blocks between the homogeneous regions, we can obtain the exact pixel-based contour. Experimental results show that the proposed algorithm yields larger segments, particularly in the textural area, and reduces the computational complexities.

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Adaptive One-Bit Transform Using Characteristic of Reference Block (참조 블록의 특성에 기반한 선택적 1비트 변환 알고리듬)

  • Park, Miso;Kim, Jaehun;Kim, Hyungdo;jeong, Jechang
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2013.11a
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    • pp.223-226
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    • 2013
  • 정확한 움직임 추정 기술은 원본과 가장 유사한 영상의 복원에 효과적이고 압축률에도 중요한 영향을 미친다. 하지만 기존의 전역 탐색 (Full Search) 알고리듬과 Sum of Absolute Difference (SAD)라는 정합 오차 기준은 연산량이 높고 하드웨어 구현시 비효율적이다. 이를 보완하기 위한 1비트 변환 알고리듬은 움직임 벡터의 변화량을 0과 1의 연산으로 나타내는데, 이 알고리듬은 움직임이 많아 픽셀 값의 변화가 심한 블록의 변화량도 0과 1로만 표현한다. 그렇기 때문에 정확한 움직임이 반영되지 않고 그로 인해 낮은 Peak Siganl to Noise Ratio (PSNR)을 가져온다. 이 점을 개선하고자 본 논문에서는 참조블록들의 움직임 벡터를 파악하고 분류하여 선택적으로 움직임의 변화량이 큰 영역은 전역 탐색 알고리듬을, 움직임이 작거나 없는 영역은 1비트 연산을 수행하도록 하여 기존의 알고리듬과 비교하여 Peak Siganl to Noise Ratio (PSNR)측면에서 우수한 성능을 확인할 수 있었다.

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Small Target Detection Method Using Bilateral Filter Based on Surrounding Statistical Feature (주위 통계 특성에 기초한 양방향 필터를 이용한 소형 표적 검출 기법)

  • Bae, Tae-Wuk;Kim, Young-Taeg
    • Journal of Korea Multimedia Society
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    • v.16 no.6
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    • pp.756-763
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    • 2013
  • Bilateral filter (BF), functioning by two Gaussian filters, domain and range filter is a nonlinear filter for sharpness enhancement and noise removal. In infrared (IR) small target detection field, the BF is designed by background predictor for predicting background not including small target. For this, the standard deviations of the two Gaussian filters need to be changed adaptively in background and target region of an infrared image. In this paper, the proposed bilateral filter make the standard deviations changed adaptively, using variance feature of mean values of surrounding block neighboring local filter window. And, in case the variance of mean values for surrounding blocks is low for any processed pixel, the pixel is classified to flat background and target region for enhancing background prediction. On the other hand, any pixel with high variance for surrounding blocks is classified to edge region. Small target can be detected by subtracting predicted background from original image. In experimental results, we confirmed that the proposed bilateral filter has superior target detection rate, compared with existing methods.

Out-of focus blur estimation using variable-sized blocks and basis images (가변블록과 기저영상을 사용한 초점불완전 열화시스템 추정기법)

  • 조충남;박상래;백준기
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1998.06a
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    • pp.81-85
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    • 1998
  • 점확산 함수(point spread function; PSF)의 정확한 추정은 복원결과가 원 영상에 얼마나 근접할 수 있는가를 결정한다는 점에서 영상처리의 중요한 연구 주제중의 하나가 된다. 본 논문에서는 PSF를 추정하기 위한 알고리즘을 제안하고, 이를 영상복원에 적용한 후 이를 기반으로 디지털 자동초점시스템을 제안한다. 초점불안전 열화시스템을 구현하기 위한 과정은 두 단계로 구성되어 있는데, 즉 입력 영상에서 에지분류를 통한 PSF 추정과, 이를 이용한 영상복원이다. 보다 구체적으로, 입력 영상에 특정 에지가 있는 임의의 크기의 블록을 선정해부면, 그 블록으로부터 자동으로 에지방향이 기저영상을 이용해서 구해지며 확산원의 크기를 추정하여 1차원 단위 계단응답과 영역을 구하여 평균한 후, 2차원 등방성 PSF를 추정한다. 마지막으로 추정된 PSF를 사용하여 복원을 수행함으로써 초점이 맞는 영상을 구한다.

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Image Retrieval algorithm based on Wavelet Transform (웨이브렛 변환에 기반한 영상 검색 알고리즘)

  • Hwang, Doh-Yeun;Park, Jeong-Ho;Lee, Sung-Ki;Park, Min-Sheik;Kwak, Hoon-Sung
    • Proceedings of the Korea Information Processing Society Conference
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    • 2001.10a
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    • pp.731-734
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    • 2001
  • 본 논문에서는 원 영상의 영역 분류와 웨이브렛 변환을 이용하여 영상의 밝기 변화에 관계없이 영상 검색이 가능한 알고리즘을 제안하였다. 이러한 방식을 통해 영상 전체에 대해 검색이 수행되지 않고, 영역 분류 결과인 블록맵과 변환 대역에서의 분산값 등 매우 소량의 정보만을 저장하고 이를 기반으로 영상 검색이 수행되므로 매우 라르고 효과적인 검색이 가능함을 실험을 통해 확인하였다.

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