• Title/Summary/Keyword: image detection system

Search Result 2,112, Processing Time 0.032 seconds

Vision-Based Roadway Sign Recognition

  • Jiang, Gang-Yi;Park, Tae-Young;Hong, Suk-Kyo
    • Transactions on Control, Automation and Systems Engineering
    • /
    • v.2 no.1
    • /
    • pp.47-55
    • /
    • 2000
  • In this paper, a vision-based roadway detection algorithm for an automated vehicle control system, based on roadway sign information on roads, is proposed. First, in order to detect roadway signs, the color scene image is enhanced under hue-invariance. Fuzzy logic is employed to simplify the enhanced color image into a binary image and the binary image is morphologically filtered. Then, an effective algorithm of locating signs based on binary rank order transform (BROT) is utilized to extract signs from the image. This algorithm performs better than those previously presented. Finally, the inner shapes of roadway signs with curving roadway direction information are recognized by neural networks. Experimental results show that the new detection algorithm is simple and robust, and performs well on real sign detection. The results also show that the neural networks used can exactly recognize the inner shapes of signs even for very noisy shapes.

  • PDF

Moving object Tracking Algorithm Based on Specific Color Detection (특정컬러정보 검출기반의 이동객체 탐색 알고리듬 구현)

  • Kim, Young-Bin;Ryu, Kwang-Ryol;Sclabassi, Robert J.
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
    • /
    • 2007.10a
    • /
    • pp.277-280
    • /
    • 2007
  • A moving object tracking algorithm for image searching based on specific color detection is proposed in this paper. That is preprocessed for a luminance variation and noise cancellation to be robust system. The motion tracking is used the difference between input image and reference image in R, G, B each channels for a moving image. The proposed method is enhanced to 15% fast in comparison with the contour tracking method and the matching method, and stable.

  • PDF

A Computationally Efficient Retina Detection and Enhancement Image Processing Pipeline for Smartphone-Captured Fundus Images

  • Elloumi, Yaroub;Akil, Mohamed;Kehtarnavaz, Nasser
    • Journal of Multimedia Information System
    • /
    • v.5 no.2
    • /
    • pp.79-82
    • /
    • 2018
  • Due to the handheld holding of smartphones and the presence of light leakage and non-balanced contrast, the detection of the retina area in smartphone-captured fundus images is more challenging than retinography-captured fundus images. This paper presents a computationally efficient image processing pipeline in order to detect and enhance the retina area in smartphone-captured fundus images. The developed pipeline consists of five image processing components, namely point spread function parameter estimation, deconvolution, contrast balancing, circular Hough transform, and retina area extraction. The results obtained indicate a typical fundus image captured by a smartphone through a D-EYE lens is processed in 1 second.

Research on Artificial Intelligence Based De-identification Technique of Personal Information Area at Video Data (영상데이터의 개인정보 영역에 대한 인공지능 기반 비식별화 기법 연구)

  • In-Jun Song;Cha-Jong Kim
    • IEMEK Journal of Embedded Systems and Applications
    • /
    • v.19 no.1
    • /
    • pp.19-25
    • /
    • 2024
  • This paper proposes an artificial intelligence-based personal information area object detection optimization method in an embedded system to de-identify personal information in video data. As an object detection optimization method, first, in order to increase the detection rate for personal information areas when detecting objects, a gyro sensor is used to collect the shooting angle of the image data when acquiring the image, and the image data is converted into a horizontal image through the collected shooting angle. Based on this, each learning model was created according to changes in the size of the image resolution of the learning data and changes in the learning method of the learning engine, and the effectiveness of the optimal learning model was selected and evaluated through an experimental method. As a de-identification method, a shuffling-based masking method was used, and double-key-based encryption of the masking information was used to prevent restoration by others. In order to reuse the original image, the original image could be restored through a security key. Through this, we were able to secure security for high personal information areas and improve usability through original image restoration. The research results of this paper are expected to contribute to industrial use of data without personal information leakage and to reducing the cost of personal information protection in industrial fields using video through de-identification of personal information areas included in video data.

A Motion Detection Approach based on UAV Image Sequence

  • Cui, Hong-Xia;Wang, Ya-Qi;Zhang, FangFei;Li, TingTing
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.12 no.3
    • /
    • pp.1224-1242
    • /
    • 2018
  • Aiming at motion analysis and compensation, it is essential to conduct motion detection with images. However, motion detection and tracking from low-altitude images obtained from an unmanned aerial system may pose many challenges due to degraded image quality caused by platform motion, image instability and illumination fluctuation. This research tackles these challenges by proposing a modified joint transform correlation algorithm which includes two preprocessing strategies. In spatial domain, a modified fuzzy edge detection method is proposed for preprocessing the input images. In frequency domain, to eliminate the disturbance of self-correlation items, the cross-correlation items are extracted from joint power spectrum output plane. The effectiveness and accuracy of the algorithm has been tested and evaluated by both simulation and real datasets in this research. The simulation experiments show that the proposed approach can derive satisfactory peaks of cross-correlation and achieve detection accuracy of displacement vectors with no more than 0.03pixel for image pairs with displacement smaller than 20pixels, when addition of image motion blurring in the range of 0~10pixel and 0.002variance of additive Gaussian noise. Moreover,this paper proposes quantitative analysis approach using tri-image pairs from real datasets and the experimental results show that detection accuracy can be achieved with sub-pixel level even if the sampling frequency can only attain 50 frames per second.

The Measurement of The Inclined Pinhole in The Cold Strip (극박 냉연강판의 경사진 핀홀 검출에 관한 연구)

  • 김하술;배호문;이희준
    • Proceedings of the Korean Society for Technology of Plasticity Conference
    • /
    • 1999.08a
    • /
    • pp.201-207
    • /
    • 1999
  • The automatic pinhole detection system is described. The goal of this project is to study the feasibility test of the new concept for hole detection. The developed method is able to detect almost 50$\mu\textrm{m}$ pinhole by evaluating the shining of the light as if there is pinhole in the strip. Moreover, it is possible to inspect up to the 200$\mu\textrm{m}$ inclined pinhole. The system cosists of three main functional parts: the source part of the light which is using the linear halogen lamp, the image gathering part which is using a line CCD and the image processing part. The light spot can be controlled and optimized corresponding to the situation of the strip. To eliminate back ground noise, the binary image processing method is adopted.

  • PDF

Detection and Recognition of Vehicle Brake Lights using an R-Filtering (R-필터링을 이용한 자동차 브레이크등 검출과 인식)

  • Jung, Min-Chul
    • Journal of the Semiconductor & Display Technology
    • /
    • v.10 no.4
    • /
    • pp.95-100
    • /
    • 2011
  • This paper proposes a new method of vehicle brake lights detection and recognition using an R-filtering. Firstly, the proposed method processes the R-filtering with the first input image and then with the second one in order to detect brake lights. Secondly, the method counts the number of red pixels and computes the mean value in each R-filtered image. The difference rates between the numbers of the red pixels and between the mean values of two images are defined in this paper. Through the analysis of the difference rates, it can recognize whether brake lights are turned on or off, and whether the vehicle ahead is being approached or not. The proposed method is implemented using C language in an embedded Linux system for a high-speed real-time image processing. Experiment results show that the proposed algorithm is quite successful.

Real-Time Traffic Information Collection Using Multiple Virtual Detection Lines (다중 가상 검지선을 이용한 실시간 교통정보 수집)

  • Kim, Eui-Chul;Kim, Soo-Hyung;Lee, Guee-Sang;Yang, Hyung-Jeong
    • The KIPS Transactions:PartB
    • /
    • v.15B no.6
    • /
    • pp.543-552
    • /
    • 2008
  • ATIS(Advanced Traveler Information System) is the system to offer a real-time traffic information or traffic situation for the benefit of the client. One of traffic information collection methods for ATIS research is the method of image analysis. The method is divided into two : one is the method to set two loop detectors at the area and the other is the method detecting the vehicle through an image analysis. In this paper, we propose a real-time traffic information collection system to mix two methods. The system installs multiple virtual detection lines and traces the location of the vehicle. Use of multiple virtual detection lines supplements the defect of the method of loop detectors. And we drew a representative pixels in the detecting area and used it for image analysis. This is to solve the problem of time delay which increases as the image size increases. We gathered traffic images and experimented using the system and got 92.32% of detection accuracy.

Automatic Sputum Color Image Segmentation for Lung Cancer Diagnosis

  • Taher, Fatma;Werghi, Naoufel;Al-Ahmad, Hussain
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.7 no.1
    • /
    • pp.68-80
    • /
    • 2013
  • Lung cancer is considered to be the leading cause of cancer death worldwide. A technique commonly used consists of analyzing sputum images for detecting lung cancer cells. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid errors. The manual screening of sputum samples has to be improved by using image processing techniques. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection and diagnosis of lung cancer based on the analysis of the sputum color image with the aim to attain a high accuracy rate and to reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a framework for segmentation and extraction of sputum cells in sputum images using respectively, a Bayesian classification method followed by region detection and feature extraction techniques to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer. We analyzed the performance of a Bayesian classification with respect to the color space representation and quantification. Our methods were validated via a series of experimentation conducted with a data set of 100 images. Our evaluation criteria were based on sensitivity, specificity and accuracy.

Detection and Diagnosis of Power Distribution Supply Facilities Using Thermal Images (열화상 이미지를 이용한 배전 설비 검출 및 진단)

  • Kim, Joo-Sik;Choi, Kyu-Nam;Lee, Hyung-Geun;Kang, Sung-Woo
    • Journal of the Korea Safety Management & Science
    • /
    • v.22 no.1
    • /
    • pp.1-8
    • /
    • 2020
  • Maintenance of power distribution facilities is a significant subject in the power supplies. Fault caused by deterioration in power distribution facilities may damage the entire power distribution system. However, current methods of diagnosing power distribution facilities have been manually diagnosed by the human inspector, resulting in continuous pole accidents. In order to improve the existing diagnostic methods, a thermal image analysis model is proposed in this work. Using a thermal image technique in diagnosis field is emerging in the various engineering field due to its non-contact, safe, and highly reliable energy detection technology. Deep learning object detection algorithms are trained with thermal images of a power distribution facility in order to automatically analyze its irregular energy status, hereby efficiently preventing fault of the system. The detected object is diagnosed through a thermal intensity area analysis. The proposed model in this work resulted 82% of accuracy of detecting an actual distribution system by analyzing more than 16,000 images of its thermal images.