• 정보처리학회논문지B
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• 제19B권2호
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• pp.127-134
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• 2012

영상디지털도어록(Video digital door lock, VDDL) 시스템은 문으로 출입하는 사람을 검출하고 사람 영상을 획득한다. 도어록 설계 시 고려할 사항은 배터리 기반으로 동작하므로 속도가 빠른 사람 검출 알고리즘을 적용하여 전류소모를 최소화해야 한다. 그리고 도어록은 고정된 카메라에서 영상을 촬영하므로 배경영상을 이용한 사람 검출이 높은 신뢰성을 얻을 수 있다. 본 논문에서는 이러한 요구조건에 충족하며 VDDL에 적합한 단일 사람검출 알고리즘을 다루고 있는데, 획득한 영상에서 이동하는 물체를 감지하고 영상처리를 통해 물체가 사람인지를 판별한다. 제안된 영상처리 알고리즘은 두 단계로 이루어져 있다. 첫째, 배경영상과 피부색 정보를 통해 사람 이미지 영역을 구한다. 둘째, 인체비례 정보를 기반으로 폴라 히스토그램을 이용하여 사람 유무를 판단한다. 개발된 알고리즘은 도어록에 설치하고 실험을 통해 성능을 확인하였다.

• 한국측량학회지
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• 제37권5호
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• pp.389-395
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• 2019

Unlike aerial images covering small region, satellite data show high potential to detect urban scale geospatial changes. The change detection using satellite images can be carried out using single image or stereo images. The single image approach is based on radiometric differences between two images of different times. It has limitations to detect building level changes when the significant occlusion and relief displacement appear in the images. In contrast, stereo satellite data can be used to generate DSM (Digital Surface Model) that contain information of relief-corrected objects. Therefore, they have high potential for the object change detection. Therefore, we carried out a study for the change detection over an urban area using stereo satellite data of two different times. First, the RPC correction was performed for two DSMs generation via stereo image matching. Then, D-DSM (Differential DSM) was generated by differentiating two DSMs. The D-DSM was used for the topographic change detection and the performance was checked by applying different height thresholds to D-DSM.

• 로봇학회논문지
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• 제8권4호
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• pp.238-246
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• 2013

In this paper, a robot vision technique is presented to detect obstacles, particularly approaching humans, in the images acquired by a mobile robot that autonomously navigates in a narrow building corridor. A single low-cost color camera is attached to the robot, and a trapezoidal area is set as a region of interest (ROI) in front of the robot in the camera image. The lower parts of a human such as feet and legs are first detected in the ROI from their appearances in real time as the distance between the robot and the human becomes smaller. Then, the human detection is confirmed by detecting his/her face within a small search region specified above the part detected in the trapezoidal ROI. To increase the credibility of detection, a final decision about human detection is made when a face is detected in two consecutive image frames. We tested the proposed method using images of various people in corridor scenes, and could get promising results. This method can be used for a vision-guided mobile robot to make a detour for avoiding collision with a human during its indoor navigation.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2020년도 추계학술발표대회
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• pp.814-817
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• 2020

The number of single-person households is increasing every year, and there are also high concerns about the crime and safety of single-person households. In particular, crimes targeting women are increasing. Although home surveillance camera applications, which are mostly used by single-person households, only provide intrusion detection functions, this service utilizes AI image recognition technologies such as face recognition and object detection to provide theft, violence, stranger and intrusion detection. Users can receive security-related notifications, relieve their anxiety, and prevent crimes through this service.

• 디지털콘텐츠학회 논문지
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• 제19권9호
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• pp.1787-1793
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• 2018

그림자는 자연 경관에서 관찰되는 일반적인 현상이지만 물체 인식, 특징 검출 및 장면 분석등과 같은 영상 분석에 부정적인 영향을 미치는 요소이므로 디지털 영상에 포함된 그림자 처리는 디지털 영상 분석 과정에서 필수적으로 고려되어야 한다. 본 논문에서는 단일 자연 영상에 포함된 그림자를 검출하고 제거하기 위한 특징 요소 중의 하나인 1D 불변 영상의 획득을 위한 기존 방법들에 대해 기술하고, 선형 회귀 기반의 1D 불변 영상 획득 방법을 제안하였다. 제안하는 방법은 RGB 칼라 영상의 각 채널 간의 밴드 비의 로그를 계산한 후 선형 회귀를 통해 그레이스케일 영상 라인을 획득하고, 최종 1D 불변 영상은 밴드 비의 로그 영상들을 추정된 그레이스케일 영상 라인으로 투영시켜 획득하였다. 실험 결과, 제안하는 방법이 기존의 엔트로피 최소화 기반의 투영 각도를 계산하는 방법보다 계산 복잡도가 낮았으며, 1D 불변 영상을 이용한 그림자가 검출 및 제거가 효과적으로 수행됨을 보였다.

• 대한원격탐사학회지
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• 제22권5호
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• pp.337-350
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• 2006

The characteristics of neighborhood correlation images for change detection were explored at different spatial resolution scales. Bi-temporal QuickBird datasets of Las Vegas, NV were used for the high spatial resolution image analysis, while bi-temporal Landsat $TM/ETM^{+}$ datasets of Suwon, South Korea were used for the mid spatial resolution analysis. The neighborhood correlation images consisting of three variables (correlation, slope, and intercept) were evaluated and compared between the two scales for change detection. The neighborhood correlation images created using the Landsat datasets resulted in somewhat different patterns from those using the QuickBird high spatial resolution imagery due to several reasons such as the impact of mixed pixels. Then, automated binary change detection was also performed using the single and multiple neighborhood correlation image variables for both spatial resolution image scales.

• International Journal of Advanced Culture Technology
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• 제8권4호
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• pp.229-234
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• 2020

Dehazing significantly improves image quality by restoring the loss of contrast and color saturation for images taken in the presence. However, when applied to images not taken according to the prior information, dehazing can cause unintended degradation of image quality. To avoid unintended degradations, we present a hazy scene detection algorithm using a single image based on the distributions of hue, saturation, and dark channel. Through a heuristic approach, we find out statistical characteristics of the distribution of hue, saturation, and dark channels in the hazy scene and make a detection model using them. The proposed method can precede the dehazing to prevent unintended degradation. The detection performance evaluated with a set of test images shows a high hit rate with a low false alarm ratio. Ultimately the proposed method can be used to control the effect of dehazing so that the dehazing can be applied to wide variety of images without unintended degradation of image quality.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.739-742
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• 2005

In this paper, an efficient detection algorithm for the flicker, which is caused by mismatching between light frequency and exposure time at CMOS image sensor (CIS), is proposed. The flicker detection can be implemented by specific hardware or complex signal processing logic. However it is difficult to implement on single chip image sensor, which has pixel, CDS, ADC, and ISP on a die, because of limited die area. Thus for the flicker detection, the simple algorithm and high accuracy should be achieved on single chip image sensor,. To satisfy these purposes, the proposed algorithm organizes only simple operation, which calculates the subtraction of horizontal luminance mean between continuous two frames. This algorithm was verified with MATLAB and Xilinx FPGA, and it is implemented with Magnachip 0.18 standard cell library. As a result, the accuracy is 95% in average on FPGA emulation and the consumed gate count is about 7,500 gates (@40MHz) for implementation using Magnachip 0.18 process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권9호
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• pp.3751-3770
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• 2015

Many sorts of image processing software facilitate image editing and also generate a great number of doctored images. Forensic technology emerges to detect the unintentional or malicious image operations. Most of forensic methods focus on the detection of single operations. However, a series of operations may be used to sequentially manipulate an image, which makes the operation detection problem complex. Forensic investigators always want to know as much exhaustive information about a suspicious image's entire processing history as possible. The detection of the operation chain, consisting of a series of operations, is a significant and challenging problem in the research field of forensics. In this paper, based on the histogram distribution uniformity of a manipulated image, we propose an operation chain detection scheme to identify histogram equalization (HE) followed by the dither-like operation (DLO). Two histogram features and a local spatial feature are utilized to further determine which DLO may have been applied. Both theoretical analysis and experimental results verify the effectiveness of our proposed scheme for both global and local scenarios.

• 한국컴퓨터정보학회논문지
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• 제22권3호
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• pp.45-51
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• 2017

In this paper, we propose a consecutive-frame super-resolution method to tackle a moving object problem. The super-resolution is a method restoring a high resolution image from a low resolution image. The super-resolution is classified into two types, briefly, single-frame super-resolution and consecutive-frame super-resolution. Typically, the consecutive-frame super-resolution recovers a better than the single-frame super-resolution, because it use more information from consecutive frames. However, the consecutive-frame super-resolution failed to recover the moving object. Therefore, we proposed an improved method via moving object detection. Experimental results showed that the proposed method restored both the moving object and the background properly.