Teaching digital image processing and computer vision in a quantitative imaging electronic classroom

1998 ◽  
Author(s):  
Milan Sonka
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Digital Image Processing ◽  
Digital Image ◽  
Quantitative Imaging ◽  
Electronic Classroom

scholarly journals A Study on Traditional and CNN Based Computer Vision Sensors for Detection and Recognition of Road Signs with Realization for ADAS

2021 ◽  
Author(s):  
Vinay M. Shivanna ◽  
Kuan-Chou Chen ◽  
Bo-Xun Wu ◽  
Jiun-In Guo
Keyword(s):  
Neural Network ◽  
Image Processing ◽  
Computer Vision ◽  
Digital Image Processing ◽  
Digital Image ◽  
Road Signs ◽  
Vision Sensors ◽  
Detection And Recognition

The aim of this chapter is to provide an overview of how road signs can be detected and recognized to aid the ADAS applications and thus enhance the safety employing digital image processing and neural network based methods. The chapter also provides a comparison of these methods.

scholarly journals Development of Hexapod Robot with Computer Vision

2021 ◽  
Vol 9 (8) ◽  
pp. 1796-1805
Author(s):  
Abhishek C
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Digital Image Processing ◽  
Digital Image ◽  
Degrees Of Freedom ◽  
Legged Locomotion ◽  
Robotic Systems ◽  
Raspberry Pi ◽  
Hexapod Robot ◽  
Irregular Surfaces

Abstract: Nowadays many robotic systems are developed with lot of innovation, seeking to get flexibility and efficiency of biological systems. Hexapod Robot is the best example for such robots, it is a six-legged robot whose walking movements try to imitate the movements of the insects, it has two sets of three legs alternatively which is used to walk, this will provide stability, flexibility and mobility to travel on irregular surfaces. With these attributes the hexapod robots can be used to explore irregular surfaces, inhospitable places, or places which are difficult for humans to access. This paper involves the development of hexapod robot with digital image processing implemented on Raspberry Pi, to study in the areas of robotic systems with legged locomotion and robotic vision. This paper is an integration of a robotic system and an embedded system of digital image processing, programmed in high level language using Python. It is equipped with a camera to capture real time video and uses a distance sensor that allow the robot to detect obstacles. The Robot is Self-Stabilizing and can detect corners. The robot has 3 degrees of freedom in each six legs thus making a 18 DOF robotic movement. The use of multiple degrees of freedom at the joints of the legs allows the legged robots to change their movement direction without slippage. Additionally, it is possible to change the height from the ground, introducing a damping and a decoupling between the terrain irregularities and the body of the robot servo motors. Keywords: Hexapod, Raspberry Pi, Computer vision, Object detection, Yolo, Servo Motor, OpevCV.

Measurement of Work Piece Surface Quality Based on Digital Image Processing

2011 ◽  
Vol 101-102 ◽  
pp. 689-692
Author(s):  
Cheng Yu Wu ◽  
Fei Qing Wu ◽  
Hui Mei Yang
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Real Time ◽  
Surface Quality ◽  
Digital Image Processing ◽  
Digital Image ◽  
Surface Flaw ◽  
Work Piece ◽  
Computer Vision Technology ◽  
Modern Image

This article discusses how to apply sensor mixture, modern image handle and computer vision technology to analyse and to deal with the feature messages of the ground work piece surface flaw, and computer how to apply the filtered feature messages to identify these flaws. Result shows that this system can find the defect work piece real time from the images for testing.

scholarly journals Computer Vision System for Welding Inspection of Liquefied Petroleum Gas Pressure Vessels Based on Combined Digital Image Processing and Deep Learning Techniques

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4505
Author(s):  
Yarens J. Cruz ◽  
Marcelino Rivas ◽  
Ramón Quiza ◽  
Gerardo Beruvides ◽  
Rodolfo E. Haber
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Deep Learning ◽  
Digital Image Processing ◽  
Digital Image ◽  
Vision System ◽  
Pressure Vessels ◽  
Liquefied Petroleum Gas ◽  
Computer Vision System ◽  
Learning Techniques

One of the most important operations during the manufacturing process of a pressure vessel is welding. The result of this operation has a great impact on the vessel integrity; thus, welding inspection procedures must detect defects that could lead to an accident. This paper introduces a computer vision system based on structured light for welding inspection of liquefied petroleum gas (LPG) pressure vessels by using combined digital image processing and deep learning techniques. The inspection procedure applied prior to the welding operation was based on a convolutional neural network (CNN), and it correctly detected the misalignment of the parts to be welded in 97.7% of the cases during the method testing. The post-welding inspection procedure was based on a laser triangulation method, and it estimated the weld bead height and width, with average relative errors of 2.7% and 3.4%, respectively, during the method testing. This post-welding inspection procedure allows us to detect geometrical nonconformities that compromise the weld bead integrity. By using this system, the quality index of the process was improved from 95.0% to 99.5% during practical validation in an industrial environment, demonstrating its robustness.

Computer Vision and Digital Image Processing in Intelligent Navigation System

2014 ◽  
Vol 687-691 ◽  
pp. 3828-3831
Author(s):  
Xin Chang Zhang ◽  
Xu Dong Jin
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Digital Image Processing ◽  
Digital Image ◽  
Navigation System ◽  
Pivotal Role ◽  
National Defense ◽  
Practical Science ◽  
The Core ◽  
Core Components

Current intelligent navigation system has been a mature practical science and technology. Computer vision and digital image processing are the core components, which play pivotal role in intelligent navigation system. These two technologies have been widely applied into national defense and traffic industry. Since extreme weather is frequent, there are higher requirement in computer vision and digital image processing technology.

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