• Title/Summary/Keyword: shadow detection

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A License Plate Detection Method Using Multiple-Color Model and Character Layout Information in Complex Background (다중색상 모델과 문자배치 정보를 이용한 복잡한 배경 영상에서의 자동차 번호판 추출)

  • Kim, Min-Ki
    • Journal of Korea Multimedia Society
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    • v.11 no.11
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    • pp.1515-1524
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    • 2008
  • This paper proposes a method that detects a license plate in complex background using a multiple-color model and character layout information. A layout of a green license plate is different from that of a white license plate. So, this study used a strategy that firstly assumes the plate color and then utilizes its layout information. At first, it extracts green areas from an input image using a multiple-color model which combined HIS and YIQ color models with RGB color model. If green areas are detected, it searches the character layout of the green plate by analyzing the connected components in each areas. If not detected, it searches the character layout of the white plate in all area. Finally, it extracts a license plate by grouping the connected components which corresponds to characters. Experimental result shows that 98.1% of 419 input images are correctly detected. It also shows that the proposed method is robust against illumination, shadow, and weather condition.

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Detecting and Tracking Vehicles at Local Region by using Segmented Regions Information (분할 영역 정보를 이용한 국부 영역에서 차량 검지 및 추적)

  • Lee, Dae-Ho;Park, Young-Tae
    • Journal of KIISE:Software and Applications
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    • v.34 no.10
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    • pp.929-936
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    • 2007
  • The novel vision-based scheme for real-time extracting traffic parameters is proposed in this paper. Detecting and tracking of vehicle is processed at local region installed by operator. Local region is divided to segmented regions by edge and frame difference, and the segmented regions are classified into vehicle, road, shadow and headlight by statistical and geometrical features. Vehicle is detected by the result of the classification. Traffic parameters such as velocity, length, occupancy and distance are estimated by tracking using template matching at local region. Because background image are not used, it is possible to utilize under various conditions such as weather, time slots and locations. It is performed well with 90.16% detection rate in various databases. If direction, angle and iris are fitted to operating conditions, we are looking forward to using as the core of traffic monitoring systems.

Queue Detection using Fuzzy-Based Neural Network Model (퍼지기반 신경망모형을 이용한 대기행렬 검지)

  • KIM, Daehyon
    • Journal of Korean Society of Transportation
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    • v.21 no.2
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    • pp.63-70
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    • 2003
  • Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

Research of the Face Extract Algorithm from Road Side Images Obtained by vehicle (차량에서 획득된 도로 주변 영상에서의 얼굴 추출 방안 연구)

  • Rhee, Soo-Ahm;Kim, Tae-Jung;Kim, Moon-Gie;Yun, Duk-Geun;Sung, Jung-Gon
    • Journal of Korean Society for Geospatial Information Science
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    • v.16 no.1
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    • pp.49-55
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    • 2008
  • The face extraction is very important to provide the images of the roads and road sides without the problem of privacy. For face extraction form roadside images, we detected the skin color area by using HSI and YCrCb color models. Efficient skin color detection was achieved by using these two models. We used a connectivity and intensity difference for grouping, skin color regions further we applied shape conditions (rate, area, number and oval condition) and determined face candidate regions. We applied thresholds to region, and determined the region as the face if black part was over 5% of the whole regions. As the result of the experiment 28 faces has been extracted among 38 faces had problem of privacy. The reasons which the face was not extracted were the effect of shadow of the face, and the background objects. Also objects with the color similar to the face were falsely extracted. For improvement, we need to adjust the threshold.

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Multi-temporal Analysis of High-resolution Satellite Images for Detecting and Monitoring Canopy Decline by Pine Pitch Canker

  • Lee, Hwa-Seon;Lee, Kyu-Sung
    • Korean Journal of Remote Sensing
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    • v.35 no.4
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    • pp.545-560
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    • 2019
  • Unlike other critical forest diseases, pine pitch canker in Korea has shown rather mild symptoms of partial loss of crown foliage and leaf discoloration. This study used high-resolution satellite images to detect and monitor canopy decline by pine pitch canker. To enhance the subtle change of canopy reflectance in pitch canker damaged tree crowns, multi-temporal analysis was applied to two KOMPSAT multispectral images obtained in 2011 and 2015. To assure the spectral consistency between the two images, radiometric corrections of atmospheric and shadow effects were applied prior to multi-temporal analysis. The normalized difference vegetation index (NDVI) of each image and the NDVI difference (${\Delta}NDVI=NDVI_{2015}-NDVI_{2011}$) between two images were derived. All negative ΔNDVI values were initially considered any pine stands, including both pitch canker damaged trees and other trees, that showed the decrease of crown foliage from 2011 to 2015. Next, $NDVI_{2015}$ was used to exclude the canopy decline unrelated to the pitch canker damage. Field survey data were used to find the spectral characteristics of the damaged canopy and to evaluate the detection accuracy from further analysis.Although the detection accuracy as assessed by limited number of field survey on 21 sites was 71%, there were also many false alarms that were spectrally very similar to the damaged canopy. The false alarms were mostly found at the mixed stands of pine and young deciduous trees, which might invade these sites after the pine canopy had already opened by any crown damages. Using both ${\Delta}NDVI$ and $NDVI_{2015}$ could be an effective way to narrow down the potential area of the pitch canker damage in Korea.

A study on inspection system for brake pad (브레이크패드 검사 시스템 구축에 관한 연구)

  • Kim, Tae-Eun
    • The Journal of the Korea institute of electronic communication sciences
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    • v.8 no.3
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    • pp.403-408
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    • 2013
  • In this paper, we propose to develop an inspection system that recognizes surface cracks on the brake pad and the types of brake pads of each car during the production process, on a conveyor belt. The brake pad is made from a mixture of materials, using high-heat and pressure. Therefore, the brake pad can be cracked and damaged on the surface during production. Our goal is to develop an effective detection system and application software to detect substandard product. A shadow is generated when the artificial light shines on the damaged of the surface of pad. Using the computer vision algorithm that is proposed we can detect the substandard product. Results from experiments confrim the performance of the proposed algorithm.

Hypothesis Generation for Vehicle Detection by Combining Shadow and Edge (그림자 및 에지 특징을 이용한 차량 후보 영역 검출)

  • Lee, Seung-Hyun;Kim, Tae-Dong;Yi, Kang;Jung, Kyeong-Hoon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2016.06a
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    • pp.267-270
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    • 2016
  • 차량 인식 기술은 지능형 자율주행 차량 및 첨단 운전자 보조 시스템 (ADAS: Advanced Driver Assistance System)의 개발에 있어서 핵심 요소 기술이다. 영상 기반의 차량 검출 알고리즘은 일반적으로 가설 생성 (HG: Hypothesis Generation) 단계와 가설 검증 (HV: Hypothesis Verification) 단계로 구성된다. 가설 검증 단계는 관심 영역 (ROI: Region of Interest) 내에 차량이 존재할 가능성이 있는 후보 영역을 만드는 단계로서 전체 알고리즘의 복잡도와 성능에 영향을 미친다. 본 논문에서는 관심 영역 내에 존재하는 그림자와 차량으로 인한 에지를 검출하고 두 특징 정보를 결합한 가설 생성 방법을 제안하고 차량 후방 영상을 이용하여 사각지대를 감시하는 시스템에 제안 방법을 적용하는 실험을 수행하였다. 실험 결과로 제안 방법이 차량 후보 영역의 존재 여부와 위치 정보를 판단하기에 적합하며 이를 통해 차량 검출 알고리즘의 계산 복잡도를 개선하면서도 다음 단계인 가설 검증 시 검출 성능을 향상시킬 수 있음을 확인하였다.

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Luminance Stabilization of Image Sequence (영상 시퀀스의 밝기변화 보정)

  • Lee, Im-Geun;Han, Soow-Han
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.7
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    • pp.1661-1666
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    • 2010
  • Due to light condition or shadow around camera, acquired image sequence is often degraded by intensity fluctuation. This artifact is called luminance flicker. As the luminance flicker corrupts the performance of motion estimation or object detection, it should be corrected before further processing. In this paper, we analyze the flicker generation model and propose the new algorithm for flicker reduction. The proposed algorithm considers gain and offset parameter separately, and stabilizes the luminance fluctuation based on these parameters. We show the performance of the proposed method by testing on the sequence with artificially added luminance flicker and real sequence with object motion.

A Study on Automatic Target Recognition Using SAR Imagery (SAR 영상을 이용한 자동 표적 식별 기법에 대한 연구)

  • Park, Jong-Il;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.11
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    • pp.1063-1069
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    • 2011
  • NCTR(Non-Cooperative Target Recognition) and ATR(Automatic Target Recognition) are methodologies to identify military targets using radar, optical, and infrared images. Among them, a strategy to recognize ground targets using synthetic aperature radar(SAR) images is called SAR ATR. In general, SAR ATR consists of three sequential stages: detection, discrimination and classification. In this paper, a modification of the polar mapping classifier(PMC) to identify inverse SAR(ISAR) images has been made in order to apply it to SAR ATR. In addition, a preprocessing scheme can mitigate the effect from the clutter, and information on the shadow is employed to improve the classification accuracy.

Analysis of Geological Lineaments with Compensation of the Sun's Azimuth Angle (태양방위각 보상에 의한 지질학적 선구조 분석)

  • Lee Jingeol;Lee Gyoubong;Hwang Sang-Gi
    • Journal of IKEEE
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    • v.3 no.2 s.5
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    • pp.178-185
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    • 1999
  • Geological structures such as fault and fracture patterns provide important information about preliminary exploration of mineralized areas and geological characterization. They may be recognized and interpreted from satellite images as line-like features usually referred to as lineaments. A proposed filtering method taking the sums azimuth angle into account is utilized, by which linear edges from low contrast areas where features extend parallel to the sun direction and in mountain shadow can be effectively extracted. Then, generalized Hough transform is applied to extract lineaments which correspond to fault and fracture patterns.

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