• Title/Summary/Keyword: Local Histogram

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Using Spatial Pyramid Based Local Descriptor for Face Recognition (공간 계층적 구조 기반 지역 기술자 활용 얼굴인식 기술)

  • Kim, Kyeong Tae;Choi, Jae Young
    • Journal of Korea Multimedia Society
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    • v.20 no.5
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    • pp.758-768
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    • 2017
  • In this paper, we present a novel method to extract face representation based on multi-resolution spatial pyramid. In our method, a face is subdivided into increasingly finer sub-regions (local regions) and represented at multiple levels of histogram representations. To cope with misaligned problem, patch-based local descriptor extraction has been also developed in a novel way. To preserve multiple levels of detail in local characteristics and also encode holistic spatial configuration, histograms from all levels of spatial pyramid are integrated by using dimensionality reduction and feature combination, leading to our spatial-pyramid face feature representation. We incorporate our proposed face features into general face recognition pipeline and achieve state-of-the-art results on challenging face recognition problems.

Adaptive local histogram modification method for dynamic range compression of infrared images

  • Joung, Jihye
    • Journal of the Korea Society of Computer and Information
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    • v.24 no.6
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    • pp.73-80
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    • 2019
  • In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

Implementation of Embedded System for a Fast Iris Identification Based on USN (고속의 홍채인식을 위한 USN기반의 임베디드 시스템 구현)

  • Kim, Shin-Hong;Kim, Shik
    • IEMEK Journal of Embedded Systems and Applications
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    • v.4 no.4
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    • pp.190-194
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    • 2009
  • Iris recognition is a biometric technology which can identify a person using the iris pattern. Recently, using iris information is used in many fields such as access control and information security. But Perform complex operations to extract features of the iris. Because high-end hardware for real-time iris recognition is required. This paper is appropriate for the embedded environment using local gradient histogram embedded system with iris feature extraction methods based on USN(Ubiquitous Sensor Network). Experimental results show that the performance of proposed method is comparable to existing methods using Gabor transform noticeably improves recognition performance and it is noted that the processing time of the local gradient histogram transform is much faster than that of the existing method and rotation was also a strong attribute.

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Text Location and Extraction for Business Cards Using Stroke Width Estimation

  • Zhang, Cheng Dong;Lee, Guee-Sang
    • International Journal of Contents
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    • v.8 no.1
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    • pp.30-38
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    • 2012
  • Text extraction and binarization are the important pre-processing steps for text recognition. The performance of text binarization strongly related to the accuracy of recognition stage. In our proposed method, the first stage based on line detection and shape feature analysis applied to locate the position of a business card and detect the shape from the complex environment. In the second stage, several local regions contained the possible text components are separated based on the projection histogram. In each local region, the pixels grouped into several connected components based on the connected component labeling and projection histogram. Then, classify each connect component into text region and reject the non-text region based on the feature information analysis such as size of connected component and stroke width estimation.

Obstacle Avoidance Navigation Using Distance Profile Histogram (거리 형태 히스토그램을 이용한 이동로보트의 장애물 회피 주행)

  • 김현태;노흥식;조영완;박민용
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.12
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    • pp.1-12
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    • 1996
  • A new local path planning algorithm using DPH (distance profile histogram) is suggested in this paper. The proposed method makes a grid type world map using distance values from multiple ultrasonic sensors and genrates local points through which the mobile robot can avoid obstcles safely. The DPH (distance profile historgram) represents geometrical arrangement of obstacles around the robot in the local polar coordinate system which is assumed to be atached to the robot. To control robot's navigation, a three-layered control structure is adopted. The proposed local path planning algorithm is placed on the top level. And a point-to-point translation controller takes the middle level. The bottom level consists of a velcoity servo and sonar driver modules which take charge of driving physical hardwares. The validity of the propsoed method is demonstated through several experiments.

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An Adaptive Histogram Equalization Based Local Technique for Contrast Preserving Image Enhancement

  • Lee, Joonwhoan;Pant, Suresh Raj;Lee, Hee-Sin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.15 no.1
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    • pp.35-44
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    • 2015
  • The main purpose of image enhancement is to improve certain characteristics of an image to improve its visual quality. This paper proposes a method for image contrast enhancement that can be applied to both medical and natural images. The proposed algorithm is designed to achieve contrast enhancement while also preserving the local image details. To achieve this, the proposed method combines local image contrast preserving dynamic range compression and contrast limited adaptive histogram equalization (CLAHE). Global gain parameters for contrast enhancement are inadequate for preserving local image details. Therefore, in the proposed method, in order to preserve local image details, local contrast enhancement at any pixel position is performed based on the corresponding local gain parameter, which is calculated according to the current pixel neighborhood edge density. Different image quality measures are used for evaluating the performance of the proposed method. Experimental results show that the proposed method provides more information about the image details, which can help facilitate further image analysis.

Color Image Enhancement Using Local Area Histogram Equalization On Segmented Regions Via Watershed Transform

  • Lertpokanont, B.;Chitwong, S.;Cheevasuvit, F.;Dejhan, K.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.192-194
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    • 2003
  • Since the details in quasi-homogeneous region will be destroyed from the conventional global image enhancement method such as histogram equalization. This defect is caused by the saturation of gray level in equalization process. So the local histogram equalization for each quasi-homogeneous region will be used in order to improve the details in the region itself. To obtain the quasi- homogeneous regions, the original image must be segmented. Here we applied the watershed transform to the interesting image. Since the watershed transform is based on mathematical morphology, therefore, the regions touch can be effectively separated. Hence two adjacent regions which have the similar gray pixels will be split off. The process will be independently applied to three different spectral images. Then three different colors are assigned to each processed image in order to produce a color composite image. By the proposed algorithm, the result image shows the better perception on image details. Therefore, the high efficiency of image classification can be obtained by using this color image.

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Real-time Haze Removal Method using Brightness Transformation based on Atmospheric Scatter Coefficient Rate and Local Histogram Equalization (대기 산란 계수 비율 기반의 밝기변환과 지역적 히스토그램 평활화를 이용한 실시간 안개 제거 방법)

  • Lee, Jae-Won;Hong, Sung-Hoon
    • Journal of Korea Multimedia Society
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    • v.19 no.1
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    • pp.10-21
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    • 2016
  • Images taken from outdoor are degraded quality by fog or haze, etc. In this paper, we propose a method that provides the visibility improved images through fog or haze removal. We proposed haze removal method that uses brightness transform based on atmospheric scatter coefficient rate with local histogram equalization. To calculate the transmission rate that indicate fog rate in original image, we use atmospheric scatter coefficient rate based on quadratic equations about haze model. And primary brightness transformed image can be obtained by using the obtained transmission rate. Also we use local histogram equalization with proposed brightness transform for effectively image visibility enhancement. Unlike existing methods, our method can process real-time with stable and effect image visibility enhancement. Proposed method use only the luminance images processed by good performance surveillance systems because it represents the real-time processing is required, black-box, digital camera and multimedia equipment is applicable. Also because it shows good performance only with the luminance images processed, Surveillance systems, black boxes, digital cameras, and multimedia devices etc, that require real-time processing can be applied.

An Edge Histogram Descriptor for MPEG-7 (MPEG-7을 위한 에지 히스토그램 서술자)

  • 박동권;전윤석;박수준;원치선
    • Journal of Broadcast Engineering
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    • v.5 no.1
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    • pp.31-40
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    • 2000
  • In this paper, we propose an edge histogram to efficiently represent the edge distribution in the image for MPEG-7. To this end, we adopt global, semi-global, and local edge histogram bins. Also, we extract the edge information from the image in terms of image blocks rather than pixels, which reduces the extraction complexity and is also applicable to the block-based compression standards such as MPEG-1, and 2. Experimental results show that the proposed method yields better retrieval accuracy and feature extraction speed comparing to other non-homogeneous texture descriptors of MPEG-7 including the wavelet-based descriptor and local edge-based descriptor.

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Efficient Human body tracking Using Similarity Of Histogram Of Intensity and Hue Local Area (국부 영역의 명도와 색상 히스토그램 유사도를 이용한 인체 추적)

  • Kwak, Nae-Joung;Song, Teuk-Seob
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.149-152
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    • 2016
  • In this paper, we propose an algorithm to track human body of input video from a single camera. The proposed method gets the difference image between gray image of input image and one of background image and also the difference image between hue image of input image and one of background image. Then we combine the results, splits foreground and background and detect human body objects. Then each object is numbered and is tracked. The proposed method tracks each object using the intensity and hue histogram of local area in objects. The proposed method is applied to video from a camera and tracked well the hided objects and the overlapped objects.

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