• Title/Summary/Keyword: 허프만

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Iterative Generalized Hough Transform using Multiresolution Search (다중해상도 탐색을 이용한 반복 일반화 허프 변환)

  • ;W. Nick Street
    • Journal of KIISE:Software and Applications
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    • v.30 no.10
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    • pp.973-982
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    • 2003
  • This paper presents an efficient method for automatically detecting objects in a given image. The GHT is a robust template matching algorithm for automatic object detection in order to find objects of various shapes. Many different templates are applied by the GHT in order to find objects of various shapes and size. Every boundary detected by the GHT scan be used as an initial outline for more precise contour-finding techniques. The main weakness of the GHT is the excessive time and memory requirements. In order to overcome this drawback, the proposed algorithm uses a multiresolution search by scaling down the original image to half-sized and quarter-sized images. Using the information from the first iterative GHT on a quarter-sized image, the range of nuclear sizes is determined to limit the parameter space of the half-sized image. After the second iterative GHT on the half-sized image, nuclei are detected by the fine search and segmented with edge information which helps determine the exact boundary. The experimental results show that this method gives reduction in computation time and memory usage without loss of accuracy.

Boundary Depth Estimation Using Hough Transform and Focus Measure (허프 변환과 초점정보를 이용한 경계면 깊이 추정)

  • Kwon, Dae-Sun;Lee, Dae-Jong;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.1
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    • pp.78-84
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    • 2015
  • Depth estimation is often required for robot vision, 3D modeling, and motion control. Previous method is based on the focus measures which are calculated for a series of image by a single camera at different distance between and object. This method, however, has disadvantage of taking a long time for calculating the focus measure since the mask operation is performed for every pixel in the image. In this paper, we estimates the depth by using the focus measure of the boundary pixels located between the objects in order to minimize the depth estimate time. To detect the boundary of an object consisting of a straight line and a circle, we use the Hough transform and estimate the depth by using the focus measure. We performed various experiments for PCB images and obtained more effective depth estimation results than previous ones.

Fast Hough circle detection using motion in video frames (동영상에서 움직임을 이용한 빠른 허프 원 찾기)

  • Won, Hye-Min;Lee, Kyoung-Mi
    • Journal of Internet Computing and Services
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    • v.11 no.6
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    • pp.31-39
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    • 2010
  • The Generalized Hough Transform(GHT) is the most used algorithm for circle detection with high accuracy. However, it requires many computation time, because many different templates are applied in order to find circles of various size. In the case of circle detection and tracking in video, the classical approach applies GHT for each frame in video and thus needs much high processing time for all frames. This paper proposes the fast GHT algorithm in video, using two consecutive frames are similar. In the proposed algorithm, a change-driven method conducts GHT only when two consecutive frames have many changes, and trajectory-based method does GHT in candidate areas and with candidate radius using circles detected in a previous frame. The algorithm can reduce computation time by reducing the number of frames, the edge count, and the number of searching circles, as factors which affects the speed of GHT. Our experimental results show that the algorithm successfully detects circles with less processing time and no loss of accuracy in video acquisited by a fixed camera and a moving camera.

Forensic Classification of Median Filtering by Hough Transform of Digital Image (디지털 영상의 허프 변환에 의한 미디언 필터링 포렌식 분류)

  • RHEE, Kang Hyeon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.5
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    • pp.42-47
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    • 2017
  • In the distribution of digital image, the median filtering is used for a forgery. This paper proposed the algorithm of a image forensics detection for the classification of median filtering. For the solution of this grave problem, the feature vector is composed of 42-Dim. The detected quantity 32, 64 and 128 of forgery image edges, respectively, which are processed by the Hough transform, then it extracted from the start-end point coordinates of the Hough Lines. Also, the Hough Peaks of the Angle-Distance plane are extracted. Subsequently, both of the feature vectors are composed of the proposed scheme. The defined 42-Dim. feature vector is trained in SVM (Support Vector Machine) classifier for the MF classification of the forged images. The experimental results of the proposed MF detection algorithm is compared between the 10-Dim. MFR and the 686-Dim. SPAM. It confirmed that the MF forensic classification ratio of the evaluated performance is 99% above with the whole test image types: the unaltered, the average filtering (3×3), the JPEG (QF=90 and 70)) compression, the Gaussian filtered (3×3 and 5×5) images, respectively.

An Enhanced Method for Detecting Iris from Smartphone Images in Real-Time (스마트폰 영상에서의 개선된 실시간 눈동자 검출 방법)

  • Kim, Seong-Hoon;Han, Gi-Tae
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.9
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    • pp.643-650
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    • 2013
  • In this paper, we propose a novel method for enhancing the detection speed and rate by reducing the computation in Hough Circle Transform on real-time iris detection of smartphone camera image. First of all, we find a face and eyes from input image to detect iris and normalize the iris region into fixed size to prevent variation of size for iris region according to distance from camera lens. Moreover, we carry out histogram equalization to get regular image in bright and dark illumination from smartphone and calculate minimal iris range that contains iris with the distance between corner of the left eye and corner of the right eye on the image. Subsequently, we can minimize the computation of iris detection by applying Hough Circle Transform on the range including the iris only. The experiment is carried out in two case with bright and dark illumination. Our proposed method represents that detection speed is 40% faster and detection rate is 14% better than existing methods.

Extraction of Intestinal Obstruction in X-Ray Images Using PCM (PCM 클러스터링을 이용한 X-Ray 영상에서 장폐색 추출)

  • Kim, Kwang Baek;Woo, Young Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.12
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    • pp.1618-1624
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    • 2020
  • Intestinal obstruction diagnosis method based on X-ray can affect objective diagnosis because it includes subjective factors of the examiner. Therefore, in this paper, a detection method of Intestinal Obstruction from X-Ray image using Hough transform and PCM is proposed. The proposed method uses Hough transform to detect straight lines from the extracted ROI of the intestinal obstruction X-Ray image and bowel obstruction is extracted by using air fluid level's morphological characteristic detected by the straight lines. Then, ROI is quantized by applying PCM clustering algorithm to the extracted ROI. From the quantized ROI, cluster group that includes bowel obstruction's characteristic is selected and small bowel regions are extracted by using object search from the selected cluster group. The proposed method of using PCM is applied to 30 X-Ray images of intestinal obstruction patients and setting the initial cluster number of PCM to 4 showed excellent performance in detection and the TPR was 81.47%.

Reduction Method of Added Information Generated by Increasing the Number of Quantizer Reconstruction Levels (양자화 복원 레벨 개수 증대로 발생되는 부가정보 감소방법)

  • Wu, Ya-Lin;Kwon, Soon-Kak;Kwon, Oh-Jun
    • Journal of Korea Multimedia Society
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    • v.13 no.8
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    • pp.1154-1162
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    • 2010
  • Because it is easy to implement the scalar quantizer, it is used in various video coding systems. Although the scalar quantizer with a large quantization stepsize can reduce the amount of data, it has disadvantage that the reconstructed picture quality is poor. In this paper, we propose an efficient method which improves the coding performance by maintaining original quantization stepsize and increasing the number of quantization reconstruction levels. Simultaneously, for the purpose of solving the problem of transmitting the added symbol informations which is used to indicate the region of quantizer reconstruction level as the number of quantizer reconstruction level is increased, we also suggest the method to reduce the added informations. Therefore, for the intra-coded picture of H.264 video coding system, we generate the huffman codes for the symbol informations of quantization reconstruction regions by 4×4(horizontal 4 pixels, vertical pixels) block unit. Furthermore, for the inter-coded picture, we also generate the huffman codes for the symbol informations of quantization reconstruction regions by 8×8 blocks and 4×4 blocks within a macroblock. Adopting this method of reducing the added information by increasing the number of quantization reconstruction region, It is shown that the coding performance can be improved at the same bitrate.

Face Detection Using A Selectively Attentional Hough Transform and Neural Network (선택적 주의집중 Hough 변환과 신경망을 이용한 얼굴 검출)

  • Choi, Il;Seo, Jung-Ik;Chien, Sung-Il
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.41 no.4
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    • pp.93-101
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    • 2004
  • A face boundary can be approximated by an ellipse with five-dimensional parameters. This property allows an ellipse detection algorithm to be adapted to detecting faces. However, the construction of a huge five-dimensional parameter space for a Hough transform is quite unpractical. Accordingly, we Propose a selectively attentional Hough transform method for detecting faces from a symmetric contour in an image. The idea is based on the use of a constant aspect ratio for a face, gradient information, and scan-line-based orientation decomposition, thereby allowing a 5-dimensional problem to be decomposed into a two-dimensional one to compute a center with a specific orientation and an one-dimensional one to estimate a short axis. In addition, a two-point selection constraint using geometric and gradient information is also employed to increase the speed and cope with a cluttered background. After detecting candidate face regions using the proposed Hough transform, a multi-layer perceptron verifier is adopted to reject false positives. The proposed method was found to be relatively fast and promising.

Hardware Design for JBIG2 Encoder on Embedded System (임베디드용 JBIG2 부호화기의 하드웨어 설계)

  • Seo, Seok-Yong;Ko, Hyung-Hwa
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.2C
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    • pp.182-192
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    • 2010
  • This paper proposes the hardware IP design of JBIG2 encoder. In order to facilitate the next generation FAX after the standardization of JBIG2, major modules of JBIG2 encoder are designed and implemented, such as symbol extraction module, Huffman coder, MMR coder, and MQ coder. ImpulseC Codeveloper and Xilinx ISE/EDK program are used for the synthesis of VHDL code. To minimize the memory usage, 128 lines of input image are processed succesively instead of total image. The synthesized IPs are downloaded to Virtex-4 FX60 FPGA on ML410 development board. The four synthesized IPs utilize 36.7% of total slice of FPGA. Using Active-HDL tool, the generated IPs were verified showing normal operation. Compared with the software operation using microblaze cpu on ML410 board, the synthesized IPs are better in operation time. The improvement ratio of operation time between the synthesized IP and software is 17 times in case of symbol extraction IP, and 10 times in Huffman coder IP. MMR coder IP shows 6 times faster and MQ coder IP shows 2.2 times faster than software only operation. The synthesized H/W IP and S/W module cooperated to succeed in compressing the CCITT standard document.

FPGA Implementation of Real-time 2-D Wavelet Image Compressor (실시간 2차원 웨이블릿 영상압축기의 FPGA 구현)

  • 서영호;김왕현;김종현;김동욱
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.7A
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    • pp.683-694
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    • 2002
  • In this paper, a digital image compression codec using 2D DWT(Discrete Wavelet Transform) is designed using the FPGA technology for real time operation The implemented image compression codec using wavelet decomposition consists of a wavelet kernel part for wavelet filtering process, a quantizer/huffman coder for quantization and huffman encoding of wavelet coefficients, a memory controller for interface with external memories, a input interface to process image pixels from A/D converter, a output interface for reconstructing huffman codes, which has irregular bit size, into 32-bit data having regular size data, a memory-kernel buffer to arrage data for real time process, a PCI interface part, and some modules for setting timing between each modules. Since the memory mapping method which converts read process of column-direction into read process of the row-direction is used, the read process in the vertical-direction wavelet decomposition is very efficiently processed. Global operation of wavelet codec is synchronized with the field signal of A/D converter. The global hardware process pipeline operation as the unit of field and each field and each field operation is classified as decomposition levels of wavelet transform. The implemented hardware used FPGA hardware resource of 11119(45%) LAB and 28352(9%) ESB in FPGA device of APEX20KC EP20k600CB652-7 and mapped into one FPGA without additional external logic. Also it can process 33 frames(66 fields) per second, so real-time image compression is possible.