• Title/Summary/Keyword: Background Edge

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Small Target Detection Using Bilateral Filter Based on Edge Component (에지 성분에 기초한 양방향 필터 (Bilateral Filter)를 이용한 소형 표적 검출)

  • Bae, Tae-Wuk;Kim, Byoung-Ik;Lee, Sung-Hak;Kim, Young-Choon;Ahn, Sang-Ho;Sohng, Kyu-Ik
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.9C
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    • pp.863-870
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    • 2009
  • Bilateral filter (BF) is a nonlinear filter for sharpness enhancement and noise removal. The BF performs the function by the two Gaussian filters, the domain filter and the range filter. To apply the BF to infrared (IR) small target detection, the standard deviation of the two Gaussian filters need to be changed adaptively between the background region and the target region. This paper presents a new BF with the adaptive standard deviation based on the analysis of the edge component of the local window, also having the variable filter size. This enables the BF to perform better and become more suitable in the field of small target detection Experimental results demonstrate that the proposed method is robust and efficient than the conventional methods.

Physiological and Subjective Measures of Anxiety with Repeated Exposure to Virtual Construction Sites at Different Heights

  • Sachini N.K. Kodithuwakku Arachchige;Harish Chander;Alana J. Turner;Alireza Shojaei;Adam C. Knight;Aaron Griffith;Reuben F. Burch;Chih-Chia Chen
    • Safety and Health at Work
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    • v.14 no.3
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    • pp.303-308
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    • 2023
  • Background: Occupational workers at altitudes are more prone to falls, leading to catastrophic outcomes. Acrophobia, height-related anxiety, and affected executive functions lead to postural instabilities, causing falls. This study investigated the effects of repeated virtual height exposure and training on cognitive processing and height-related anxiety. Methods: Twenty-eight healthy volunteers (age 20.48 ± 1.26 years; mass 69.52 ± 13.78 kg) were recruited and tested in seven virtual environments (VE) [ground (G), 2-story altitude (A1), 2-story edge (E1), 4-story altitude (A2), 4-story edge (E2), 6-story altitude (A3), and 6-story edge (E3)] over three days. At each VE, participants identified occupational hazards present in the VE and completed an Attitude Towards Heights Questionnaire (ATHQ) and a modified State-Trait Anxiety Inventory Questionnaire (mSTAIQ). The number of hazards identified and the ATHQ and mSTAIQ scores were analyzed using a 7 (VE; G, A1, A2, A3, E1, E2, E3) x 3 (DAY; DAY 1, DAY 2, DAY 3) factorial repeated measures analysis of variance. Results: The participants identified the lowest number of hazards at A3 and E3 VEs and on DAY 1 compared to other VEs and DAYs. ATHQ scores were lowest at G, A1, and E1 VEs. Conclusion: Cognitive processing is negatively affected by virtual altitudes, while it improves with short-term training. The features of virtual reality, such as higher involvement, engagement, and reliability, make it a better training tool to be considered in ergonomic settings. The findings of this study will provide insights into cognitive dual-tasking at altitude and its challenges, which will aid in minimizing occupational falls.

Effects of Differential Distribution of Microvessel Density, Possibly Regulated by miR-374a, on Breast Cancer Prognosis

  • Li, Jian-Yi;Zhang, Yang;Zhang, Wen-Hai;Jia, Shi;Kang, Ye;Tian, Rui
    • Asian Pacific Journal of Cancer Prevention
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    • v.14 no.3
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    • pp.1715-1720
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    • 2013
  • Background: The discovery that microRNAs (miRNAs) regulate proliferation, invasion and metastasis provides a principal molecular basis of tumor heterogeneity. Microvessel distribution is an important characteristic of solid tumors, with significant hypoxia occurring in the center of tumors with low blood flow. The distribution of miR-374a in breast tumors was examined as a factor likely to be important in breast cancer progression. Methods: Breast tissue samples from 40 patients with breast cancer were classified into two groups: a highly invasive and metastatic group (HIMG) and a low-invasive and metastatic Group (LIMG). Samples were collected from the center and edge of each tumor. In each group, six specimens were examined by microRNA array, and the remaining 14 specimens were used for real-time RT-qPCR, Western blot and immunohistochemical analyses. Correlation analysis was performed for the miRNAs and target proteins. Follow-up was carried out during 28 months to 68 months after surgery, and survival data were analyzed. Results: In the LIMG, the relative content of miR-374a was lower in the center of the tumor than at its edge; in the HIMG, it was lower at the edge of the tumor, and miR-374a levels were lower in breast cancer tissues than in normal tissues. There was no difference between VEGF-A and VCAM-1 mRNA levels at the edge and center of the tumor; however, we observed a significant difference between VEGF-A and VCAM-1 protein expression levels in these two regions. There was a negative correlation between miR-374a and target protein levels. The microvessel density (MVD) was lower in the center of the tumor than at its edge in HIMG, but the LIMG vessels were uniformly distributed. There was a significant positive correlation between MVD and the number of lymph node metastases (Pearson correlation, r=0.912, P<0.01). The median follow-up time was 48.5 months. LIMG had higher rate of disease-free survival (100%, P=0.013) and longer median survival time (66 months) than HIMG, which had a lower rate of 75% and shorter median survival time (54 months). Conclusions: Our data demonstrated miR-374a to be differentially distributed in breast cancer; VEGF-A and VCAM-1 mRNA had coincident distribution, and the distribution of teh respective proteins was uneven and opposite to that for the miR-374a. These data might explain the differences in the distribution of MVD in breast cancer and variation in breast cancer prognosis.

Optimized Hardware Design using Sobel and Median Filters for Lane Detection

  • Lee, Chang-Yong;Kim, Young-Hyung;Lee, Yong-Hwan
    • Journal of Advanced Information Technology and Convergence
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    • v.9 no.1
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    • pp.115-125
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    • 2019
  • In this paper, the image is received from the camera and the lane is sensed. There are various ways to detect lanes. Generally, the method of detecting edges uses a lot of the Sobel edge detection and the Canny edge detection. The minimum use of multiplication and division is used when designing for the hardware configuration. The images are tested using a black box image mounted on the vehicle. Because the top of the image of the used the black box is mostly background, the calculation process is excluded. Also, to speed up, YCbCr is calculated from the image and only the data for the desired color, white and yellow lane, is obtained to detect the lane. The median filter is used to remove noise from images. Intermediate filters excel at noise rejection, but they generally take a long time to compare all values. In this paper, by using addition, the time can be shortened by obtaining and using the result value of the median filter. In case of the Sobel edge detection, the speed is faster and noise sensitive compared to the Canny edge detection. These shortcomings are constructed using complementary algorithms. It also organizes and processes data into parallel processing pipelines. To reduce the size of memory, the system does not use memory to store all data at each step, but stores it using four line buffers. Three line buffers perform mask operations, and one line buffer stores new data at the same time as the operation. Through this work, memory can use six times faster the processing speed and about 33% greater quantity than other methods presented in this paper. The target operating frequency is designed so that the system operates at 50MHz. It is possible to use 2157fps for the images of 640by360 size based on the target operating frequency, 540fps for the HD images and 240fps for the Full HD images, which can be used for most images with 30fps as well as 60fps for the images with 60fps. The maximum operating frequency can be used for larger amounts of the frame processing.

Two-wheeler Detection System using Histogram of Oriented Gradients based on Local Correlation Coefficients and Curvature

  • Lee, Yeunghak;Kim, Taesun;Shim, Jaechang
    • Journal of Multimedia Information System
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    • v.2 no.4
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    • pp.303-310
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    • 2015
  • Vulnerable road users such as bike, motorcycle, small automobiles, and etc. are easily attacked or threatened with bigger vehicles than them. So this paper suggests a new approach two-wheelers detection system riding on people based on modified histogram of oriented gradients (HOGs) which is weighted by curvature and local correlation coefficient. This correlation coefficient between two variables, in which one is the person riding a bike and other is its background, can represent correlation relation. First, we extract edge vectors using the curvature of Gaussian and Histogram of Oriented Gradients (HOG) which includes gradient information and differential magnitude as cell based. And then, the value, which is calculated by the correlation coefficient between the area of each cell and one of bike, can be used as the weighting factor in process for normalizing the HOG cell. This paper applied the Adaboost algorithm to make a strong classification from weak classification. The experimental results validate the effectiveness of our proposed algorithm show higher than that of the traditional method and under challenging, such as various two-wheeler postures, complex background, and even conclusion.

Lane Detection and Tracking Algorithm for 3D Fluorescence Image Analysis (3D 형광이미지 분석을 위한 레인 검출 및 추적 알고리즘)

  • Lee, Bok Ju;Moon, Hyuck;Choi, Young Kyu
    • Journal of the Semiconductor & Display Technology
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    • v.15 no.1
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    • pp.27-32
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    • 2016
  • A new lane detection algorithm is proposed for the analysis of DNA fingerprints from a polymerase chain reaction (PCR) gel electrophoresis image. Although several research results have been previously reported, it is still challenging to extract lanes precisely from images having abrupt background brightness difference and bent lanes. We propose an edge based algorithm for calculating the average lane width and lane cycle. Our method adopts sub-pixel algorithm for extracting rising-edges and falling edges precisely and estimates the lane width and cycle by using k-means clustering algorithm. To handle the curved lanes, we partition the gel image into small portions, and track the lane centers in each partitioned image. 32 gel images including 534 lanes are used to evaluate the performance of our method. Experimental results show that our method is robust to images having background difference and bent lanes without any preprocessing.

Image Separation of Talker from a Background by Differential Image and Contours Information (차영상 및 윤곽선에 의한 배경에서 화자분리)

  • Park Jong-Il;Park Young-Bum;Yoo Hyun-Joong
    • The KIPS Transactions:PartB
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    • v.12B no.6 s.102
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    • pp.671-678
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    • 2005
  • In this paper, we suggest an algorithm that allows us to extract the important obbject from motion pictures and then replace the background with arbitrary images. The suggested technique can be used not only for protecting privacy and reducing the size of data to be transferred by removing the background of each frame, but also for replacing the background with user-selected image in video communication systems including mobile phones. Because of the relatively large size of image data, digital image processing usually takes much of the resources like memory and CPU. This can cause trouble especially for mobile video phones which typically have restricted resources. In our experiments, we could reduce the requirements of time and memory for processing the images by restricting the search area to the vicinity of major object's contour found in the previous frame based on the fact that the movement of major object is not wide or rapid in general. Specifically, we detected edges and used the edge image of the initial frame to locate candidate-object areas. Then, on the located areas, we computed the difference image between adjacent frames and used it to determine and trace the major object that might be moving. And then we computed the contour of the major object and used it to separate major object from the background. We could successfully separate major object from the background and replate the background with arbitrary images.

Dynamic Hand Gesture Recognition using Guide Lines (가이드라인을 이용한 동적 손동작 인식)

  • Kim, Kun-Woo;Lee, Won-Joo;Jeon, Chang-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.5
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    • pp.1-9
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    • 2010
  • Generally, dynamic hand gesture recognition is formed through preprocessing step, hand tracking step and hand shape detection step. In this paper, we present advanced dynamic hand gesture recognizing method that improves performance in preprocessing step and hand shape detection step. In preprocessing step, we remove noise fast by using dynamic table and detect skin color exactly on complex background for controling skin color range in skin color detection method using YCbCr color space. Especially, we increase recognizing speed in hand shape detection step through detecting Start Image and Stop Image, that are elements of dynamic hand gesture recognizing, using Guideline. Guideline is edge of input hand image and hand shape for comparing. We perform various experiments with nine web-cam video clips that are separated to complex background and simple background for dynamic hand gesture recognition method in the paper. The result of experiment shows similar recognition ratio but high recognition speed, low cpu usage, low memory usage than recognition method using learning exercise.

3-D Building Reconstruction from Standard IKONOS Stereo Products in Dense Urban Areas (IKONOS 컬러 입체영상을 이용한 대규모 도심지역의 3차원 건물복원)

  • Lee, Suk Kun;Park, Chung Hwan
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.3D
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    • pp.535-540
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    • 2006
  • This paper presented an effective strategy to extract the buildings and to reconstruct 3-D buildings using high-resolution multispectral stereo satellite images. Proposed scheme contained three major steps: building enhancement and segmentation using both BDT (Background Discriminant Transformation) and ISODATA algorithm, conjugate building identification using the object matching with Hausdorff distance and color indexing, and 3-D building reconstruction using photogrammetric techniques. IKONOS multispectral stereo images were used to evaluate the scheme. As a result, the BDT technique was verified as an effective tool for enhancing building areas since BDT suppressed the dominance of background to enhance the building as a non-background. In building recognition, color information itself was not enough to identify the conjugate building pairs since most buildings are composed of similar materials such as concrete. When both Hausdorff distance for edge information and color indexing for color information were combined, most segmented buildings in the stereo images were correctly identified. Finally, 3-D building models were successfully generated using the space intersection by the forward RFM (Rational Function Model).

License Plate Recognition System Using Hotelling Transform (호텔링 변환을 이용한 자동차 번호판 인식시스템에 관한 연구)

  • Kim, Tae-Woo;Kang, Yong-Seok
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.2 no.1
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    • pp.29-35
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    • 2009
  • In this paper by using the image taken from the rear of the vehicle to effectively extract the license plate and how to recognize the characters appearing in the offer. How to existing research on the entire video by following the pre-edge (edge) images to obtain yijinhwa. Qualified heopeu in a binary image (Hough) to convert the horizontal and vertical lines to obtain, using the characteristics of the plates to extract the license plate area. The problem with this method, the processing time is so difficult to handle real-time status of irregular points, and visual contrast with yagangwan border does not appear in the plates to extract the license plate area is that it is not. In addition, the rear of the vehicle license plate area from images taken using the characteristics of the plates myeongamgap changes sutjapok in the area, background area and the number number area of the region confirmed the contrast of the car and identified the number and the number of 42 of distance to extract the license plate area. How to research, the existing damage to the border of the plate to fail to extract the license plate area, a matter of hours to resolve problems in real-time, practical application is processed. Chapter 100 as the results of the experiment the sample video image in a car that far experiment results automatically read license plates have been able to extract the license plate and failing to represent 13% of images, character recognition result of failing to represent the image was 0.4%

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