Random Line Segment Distance Measurement Using Image Processing

2019 ◽  
Author(s):  
Sharada Naik ◽  
Shilpa Sondkar
Keyword(s):  
Image Processing ◽  
Line Segment ◽  
Distance Measurement ◽  
Random Line

scholarly journals Android Application Implemented for Distance Measurement using Image Processing

IJARCCE ◽  
2017 ◽  
Vol 6 (6) ◽  
pp. 406-409
Author(s):  
Mr. Ghumare Amar Ashok ◽  
Dr. Jadhavar J ◽  
Prof. Mulajkar R.M
Keyword(s):  
Image Processing ◽  
Distance Measurement ◽  
Android Application

scholarly journals An Accurate Scheme for Distance Measurement using an Ordinary Webcam

2017 ◽  
Vol 7 (1) ◽  
pp. 209
Author(s):  
Hossein Zivarian ◽  
Mohammad Hossein Doost Mohammadi
Keyword(s):  
Image Processing ◽  
Machine Vision ◽  
Laser Light ◽  
Defense Industry ◽  
Distance Measurement ◽  
Scientific Field ◽  
Accuracy Rate ◽  
Computer Aided ◽  
Laser Transmitter ◽  
Accurate Scheme

Nowadays, image processing has become one of the widely used computer aided science. Two major branches of this scientific field are image enhancement and machine vision. Machine vision has many applications and demands in robotic and defense industries. Detecting distance of objects is one of the extensive research in the defense industry and robotic industries that a lot of annual projects have been involved in this issue both inside and outside the country. So, in this paper, an accurate algorithm is presented for measuring the distance of the objects from a camera. In this method, a laser transmitter is used alongside a regular webcam. The laser light is transmitted to the desired object and then the distance of the object is calculated using image processing methods and mathematical and geometric relations. The performance of the proposed algorithm was evaluated using MATLAB software. The accuracy rate of distance detection is up to 99.62%. The results also has shown that the presented algorithms make the obstacle distance measurement more reliable. Finally, the performance of the proposed algorithm was compared with other methods from different literatures.

Line segment detection via random line fitting

2020 ◽  
Author(s):  
Ke Shang ◽  
Tao Lei ◽  
Quan Wang ◽  
Yu Zhang ◽  
Hao Zhang ◽  
...  
Keyword(s):  
Line Segment ◽  
Random Line ◽  
Line Segment Detection ◽  
Line Fitting

Measurement Technology Research on Target and Projectiles’ Miss Distance Based on Digital Image Processing

2011 ◽  
Vol 383-390 ◽  
pp. 4987-4993
Author(s):  
Zhi Qiang Ma ◽  
Shi Yu Sun ◽  
Yuan Zeng Cheng ◽  
Chun Ping Wang
Keyword(s):  
Image Processing ◽  
Edge Detection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Template Matching ◽  
Distance Measurement ◽  
Processing Technology ◽  
Measurement Technology ◽  
Image Processing Technology ◽  
Miss Distance

At the closed-loop calibration research of anti-aircraft weapons systems, the miss distance between target and projectiles is difficult to obtain accurately. In order to solve this problem, this paper provided using the digital image processing technology to research the miss distance measurement methods, focusing on the image filtering technology, edge detection technology and target recognition technology. According to the simulation results, the paper selected the adaptive median filtering to remove image noise, adopted the edge detection method based on the iterative threshold to obtain target edge and used template matching technology to identify the target in the image. Finally, according to the principle of image measurement technique, using centroid tracking measurement technology to achieve the miss distance measurement. The application of digital image processing technology makes the miss distance measurement become simple, effective and convenient. This measurement method enables to save money, improve accuracy, get results in real time and have a high research value.

scholarly journals DETECTION AND LOCALIZATION OF TRAFFIC LIGHTS USING YOLOV3 AND STEREO VISION

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 1247-1252
Author(s):  
W. Omar ◽  
I. Lee ◽  
G. Lee ◽  
K. M. Park
Keyword(s):  
Image Processing ◽  
Autonomous Driving ◽  
Distance Measurement ◽  
Stereo Image ◽  
Detection Accuracy ◽  
Disparity Map ◽  
Traffic Light ◽  
Stereo Camera ◽  
Traffic Lights ◽  
Time Operation

Abstract. This paper focus on traffic light distance measurement using stereo camera which is a very important and challenging task in image processing domain, where it is used in several systems such as Driving Safety Support Systems (DSSS), autonomous driving and traffic mobility. In this paper, we propose an integrated traffic light distance measurement system for self-driving based on stereo image processing. Therefore, an algorithm to spatially locate the detected traffic light is required in order to make these detections useful. In this paper, an algorithm to detect, classify the traffic light colours and spatially locate traffic light are integrated. Detection and colours classification are made simultaneously via YOLOv3, using RGB images. 3D traffic light localization is achieved by estimating the distance from the vehicle to the traffic light, by looking at detector 2D bounding boxes and the disparity map generated by stereo camera. Moreover, Gaussian YOLOv3 weights based on KITTI and Berkeley datasets has been replaced with the COCO dataset. Therefore, a detection algorithm that can cope with mislocalizations is required in autonomous driving applications. This paper proposes an integrated method for improving the detection accuracy and traffic lights colours classification while supporting a real-time operation by modelling the bounding box (bbox) of YOLOv3. The obtained results show fair results within 20 meters away from the sensor, while misdetection and classification appeared in further distance.

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