• Title/Summary/Keyword: 기울기 탐색

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A Simulation Study on the Fast Gradient-based Peak Searching Method (기울기 기반 빠른 정상점 탐색에 대한 연구)

  • Ahn, Jung-Ho
    • Journal of Digital Contents Society
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    • v.11 no.1
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    • pp.39-45
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    • 2010
  • In this paper we propose a new fast peak searching method using the gradient and present simulation results. The proposed method is a solution to the problem that finds the peak(maximum) of the unimodal function on a finite interval with minimum searching steps. Its main application is the auto-focus in the mobile phone. We propose the three steps to find the peak; periodic search, gradient-based search and detail search. In simulation we generated the Gaussian functions with white noise and have the result of about 8 searching steps and 1.04 errors on average.

Baseline Searching Method for Document Skew Detection (문서 영상의 기울기 검출을 위한 기준선 탐색 기법)

  • Shin, Myoung-Jin;Kim, Do-Hyeon;Cha, Eui-Young
    • Journal of Korea Multimedia Society
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    • v.10 no.2
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    • pp.218-225
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    • 2007
  • This paper presents a technique to detect a document skew that often occurs during document scanning. To correct a skewed document is essential for automatic processing system including character segmentation, character recognition and so on. The proposed algorithm can detect a skew angle exactly by searching characters baselines that have slant information of the document within a candidated area. To reduce processing time, we resized the image small and then established a ROI (region of interest) by morphology operations and connected components analysis. We compared our method with the existing method based on morphology operations and proved correctness and efficiency of the proposed algorithm through experiments and analysis with various kind of document images.

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Fast Fractal Image Compression Using the outer fence acceleration (블락 외곽선의 기울기를 이용한 프랙탈 이미지 압축)

  • 박인영;위영철
    • Proceedings of the Korean Information Science Society Conference
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    • 2002.10d
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    • pp.454-456
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    • 2002
  • 압축 방법에는 크게 손실(lossy)압축과 무손실(lossless)압축으로 나눌 수 있다. 그 중 프랙탈 이미지 압축은 lossy 압축의 한가지 방법으로서 개별적인 화소들에 대한 자료를 저장하기보다는, 영상 생성을 위한 명령이나 방식을 저장하는 방법이다. 특히 이미지의 내에 자기유사성(self-similarity)과 중복성(Redundancy)을 이용하여 관련성을 발견하고 수학적인 공식으로 표현하려는 방식이다. 그러나 이미지를 Domain과 Range로 블록화 한 후 유사한 이미지를 찾아내는 데 걸리는 시간이 상당히 길다. 여기에서는 Domain과 Range의 외곽선의 기울기의 부호를 이용하여 블록을 16가지로 클래스화 하여서, 전체의 Domain 블록을 탐색하는 데 걸리는 시간을 줄이고자 하였다. 전체 탐색을 하는 경우보다 10배 이상의 속도향상을 보였고, 이미지에 따라서는 PSNR 값의 손실도 없음을 보였다.

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Skew Correction of Document Images using Edge (에지를 이용한 문서영상의 기울기 보정)

  • Ju, Jae-Hyon;Oh, Jeong-Su
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.7
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    • pp.1487-1494
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    • 2012
  • This paper proposes an algorithm detecting the skew of the degraded as well as the clear document images using edge and correcting it. The proposed algorithm detects edges in a character region selected by image complexity and generates projection histograms by projecting them to various directions. And then it detects the document skew by estimating the edge concentrations in the histograms and corrects the skewed document image. For the fast skew detection, the proposed algorithm uses downsampling and 3 step coarse-to-fine searching. In the skew detection of the clear and the degraded images, the maximum and the average detection errors in the proposed algorithm are about 50% of one in a conventional similar algorithm and the processing time is reduced to about 25%. In the non-uniform luminance images acquired by a mobile device, the conventional algorithm can't detect skews since it can't get valid binary images, while the proposed algorithm detect them with the average detection error of 0.1o or under.

Design of Efficient Gradient Orientation Bin and Weight Calculation Circuit for HOG Feature Calculation (HOG 특징 연산에 적용하기 위한 효율적인 기울기 방향 bin 및 가중치 연산 회로 설계)

  • Kim, Soojin;Cho, Kyeongsoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.11
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    • pp.66-72
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    • 2014
  • Histogram of oriented gradient (HOG) feature is widely used in vision-based pedestrian detection. The interpolation is the most important technique in HOG feature calculation to provide high detection rate. In interpolation technique of HOG feature calculation, two nearest orientation bins to gradient orientation for each pixel and the corresponding weights are required. In this paper, therefore, an efficient gradient orientation bin and weight calculation circuit for HOG feature is proposed. In the proposed circuit, pre-calculated values are defined in tables to avoid the operations of tangent function and division, and the size of tables is minimized by utilizing the characteristics of tangent function and weights for each gradient orientation. Pipeline architecture is adopted to the proposed circuit to accelerate the processing speed, and orientation bins and the corresponding weights for each pixel are calculated in two clock cycles by applying efficient coarse and fine search schemes. Since the proposed circuit calculates gradient orientation for each pixel with the interval of $1^{\circ}$ and determines both orientation bins and weights required in interpolation technique, it can be utilized in HOG feature calculation to support interpolation technique to provide high detection rate.

Initialization of Cost Function for ML-Based DOA Estimation (ML 알고리즘 기반의 도래각 추정을 위한 비용 함수의 초기화 방법 비교)

  • Jo, Sang-Ho;Lee, Joon-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.1C
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    • pp.110-116
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    • 2008
  • Maximum likelihood(ML) diretion-of-arrival(DOA) estimation is essentially optimization of multivariable nonlinear cost function. Since the final estimate is highly dependent on the initial estimate, an initialization is critical in nonlinear optimization. We propose a multi-dimensional(M-D) search scheme of uniform exhaustive search and improved exhaustive search. Improved exhaustive search is superior to uniform exhaustive search in terms of the computational complexity and the accuracy of the estimates.

A Study Efficient Vanishing Point Detection Method using an Hough Transform (허프변환을 이용한 효율적인 소실점 검출방법에 대한 연구)

  • Jung, Su-Min;Kim, Jae-Seoung;Whang-Bo, Taek-Guaen
    • Proceedings of the Korea Information Processing Society Conference
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    • 2013.05a
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    • pp.367-370
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    • 2013
  • 단일 영상에서 3차원 정보를 획득하기 위해 가장 많이 사용되는 단서로는 소실점이 있다. 본 논문에서는 소실점을 추정하기 위해서 허프변환을 사용하여, 단일 영상의 소실점 탐색 시 유효 직선간의 기울기 값 비교 및 근접도를 구하여 교점 생성에 필요 없는 정보를 제거함으로서 소실점 추정 정확도를 높인 보다 정확한 소실점 탐색 기법을 제안하였다.

A Study on the Improvement of the Facial Image Recognition by Extraction of Tilted Angle (기울기 검출에 의한 얼굴영상의 인식의 개선에 관한 연구)

  • 이지범;이호준;고형화
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.7
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    • pp.935-943
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    • 1993
  • In this paper, robust recognition system for tilted facial image was developed. At first, standard facial image and lilted facial image are captured by CCTV camera and then transformed into binary image. The binary image is processed in order to obtain contour image by Laplacian edge operator. We trace and delete outermost edge line and use inner contour lines. We label four inner contour lines in order among the inner lines, and then we extract left and right eye with known distance relationship and with two eyes coordinates, and calculate slope information. At last, we rotate the tilted image in accordance with slope information and then calculate the ten distance features between element and element. In order to make the system invariant to image scale, we normalize these features with distance between left and righ eye. Experimental results show 88% recognition rate for twenty five face images when tilted degree is considered and 60% recognition rate when tilted degree is not considered.

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Facial Feature Detection Method within the Skewed Facial Images (기울어진 얼굴 영상에서 얼굴 구성 요소 추출 방법)

  • 김익환;송호근
    • Proceedings of the Korean Information Science Society Conference
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    • 2001.10b
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    • pp.436-438
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    • 2001
  • 본 논문에서는 기울어진 얼굴 영상에서 얼굴 구성 요소를 추출하는 방법을 제안한다. 제안하는 방법은 먼저 피부 색상 정보를 이용하여 얼굴 후보 영역을 추출한다. 이때 YIQ 색상 좌표계를 이용하고 조명의 영향을 반영하기 위하여 피부색상 영역을 다단계로 분할하여 색상 영역을 각각 결정한 뒤 적중률을 계산하여 얼굴 후보 영역을 결정하는 방법을 제안하였다. 2단계에서는 얼굴의 구성 요소중 가장 두드러진 특징인 눈동자 영역을 기준으로 한국인의 표준 얼굴 통계치를 적응하여 탐색하는 방법을 사용하였다. 이때 탐색된 눈동자 좌표로부터 얼굴의 기울기를 추정한다. 다음 단계에서는 얼굴 후보 영역에 대하여 기울어짐 보정을 수행한 뒤, 수평 수직 투영값을 이용하여 얼굴의 구성요소를 탐색한 뒤 얼굴 포함 최소 사각형을 정의하였다. 마지막으로 얼굴 영상 데이터 베이스로부터 얼굴 포함 최소 사각형에 대한 명암값 표준템플릿을 정의하고, 입력 영상에서 탐색된 최소 포함 사각형에 대하여 얼굴 영역 검증하는 방법을 제안하였다.

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Boundary Noise Removal and Hole Filling Algorithm for Virtual Viewpoint Image Generation (가상시점 영상 생성을 위한 경계 잡음 제거와 홀 채움 기법)

  • Ko, Min-Soo;Yoo, Ji-Sang
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.8A
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    • pp.679-688
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    • 2012
  • In this paper, performance improved hole-filling algorithm including boundary noise removing pre-process which can be used for an arbitrary view synthesis with given two views is proposed. Boundary noise usually occurs because of the boundary mismatch between the reference image and depth map and common-hole is defined as the occluded region. These boundary noise and common-hole created while synthesizing a virtual view result in some defects and they are usually very difficult to be completely recovered by using only given two images as references. The spiral weighted average algorithm gives a clear boundary of each object by using depth information and the gradient searching algorithm is able to preserve details. In this paper, we combine these two algorithms by using a weighting factor ${\alpha}$ to reflect the strong point of each algorithm effectively in the virtual view synthesis process. The experimental results show that the proposed algorithm performs much better than conventional algorithms.