Real-time measurement of traffic queue parameters by using image processing techniques

1995 ◽  
Author(s):  
M.Y. Siyal
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Time Measurement ◽  
Image Processing Techniques ◽  
Real Time Measurement ◽  
Processing Techniques

Image Enhancement Techniques Using Particle Swarm Optimization Technique

2015 ◽  
pp. 327-347 ◽  
Author(s):  
V. Santhi ◽  
B. K. Tripathy
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Particle Swarm Optimization ◽  
Real Time ◽  
Quality Enhancement ◽  
Swarm Optimization ◽  
Image Processing Techniques ◽  
Real Time Applications ◽  
High Level ◽  
Processing Techniques

The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of images and they can be carried out either in spatial domain or in frequency domain. But in real time applications, the quality enhancement process carried out by classical approaches may not serve the purpose. It is required to combine the concept of computational intelligence with the classical approaches to meet the requirements of real-time applications. In recent days, Particle Swarm Optimization (PSO) technique is considered one of the new approaches in optimization techniques and it is used extensively in image processing and pattern recognition applications. In this chapter, image enhancement is considered an optimization problem, and different methods to solve it through PSO are discussed in detail.

scholarly journals Controlling Longitudinal Safe Distance Between Vehicles

2012 ◽  
Vol 21 (5) ◽  
pp. 303-310 ◽  
Author(s):  
Seyyed Mohammad Sadat Hoseini ◽  
Mahmmood Fathi ◽  
Manouchehr Vaziri
Keyword(s):  
Image Processing ◽  
Real Time ◽  
High Technology ◽  
Safe Distance ◽  
Main Concept ◽  
Average Speed ◽  
Image Processing Techniques ◽  
Online System ◽  
Police Agencies ◽  
Processing Techniques

Controlling the safe distances between vehicles on freeways can be used to prevent many accidents. In this research, image-processing techniques have been used to develop an online system that calculates the longitudinal distances between vehicles. This system facilitates controlling safe distances between vehicles without the need for high technology devices. Our approach is real-time and simple, but efficient operations have been used to reduce the image occlusion problem. The main concept of this system is using simple, quick, and effective algorithms for calculating the position of each vehicle in each image. In this way, traffic parameters like speed and distances between vehicles can be calculated for each vehicle in real time. In addition, aggregate parameters like average speed, density, and traffic flow can be calculated using gathered data of single vehicles. As an application of the developed system, controlling the safe distance between vehicles has been introduced. In this system, in case of a driver who does not observe the safe distance, the scene of violation is stored and can be used by the police agencies. KEY WORDS: image processing, traffic, longitudinal safe distance, real time, occlusion

Image Enhancement Techniques Using Particle Swarm Optimization Technique

2015 ◽  
pp. 860-878
Author(s):  
V. Santhi ◽  
B. K. Tripathy
Keyword(s):  
Image Processing ◽  
Pattern Recognition ◽  
Particle Swarm Optimization ◽  
Real Time ◽  
Quality Enhancement ◽  
Swarm Optimization ◽  
Image Processing Techniques ◽  
Real Time Applications ◽  
High Level ◽  
Processing Techniques

The image quality enhancement process is considered as one of the basic requirement for high-level image processing techniques that demand good quality in images. High-level image processing techniques include feature extraction, morphological processing, pattern recognition, automation engineering, and many more. Many classical enhancement methods are available for enhancing the quality of images and they can be carried out either in spatial domain or in frequency domain. But in real time applications, the quality enhancement process carried out by classical approaches may not serve the purpose. It is required to combine the concept of computational intelligence with the classical approaches to meet the requirements of real-time applications. In recent days, Particle Swarm Optimization (PSO) technique is considered one of the new approaches in optimization techniques and it is used extensively in image processing and pattern recognition applications. In this chapter, image enhancement is considered an optimization problem, and different methods to solve it through PSO are discussed in detail.

Remote Sensing of Bridge Displacement Using Digital Image Processing Techniques

2006 ◽  
Vol 321-323 ◽  
pp. 404-409 ◽  
Author(s):  
Jong Jae Lee ◽  
Masanobu Shinozuka ◽  
Soo Jin Cho
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Digital Image Processing ◽  
Digital Image ◽  
Shaking Table Test ◽  
Field Tests ◽  
Video Camera ◽  
Shaking Table ◽  
Image Processing Techniques ◽  
Processing Techniques

In this study, an optical method of real-time displacement measurement of such bridges was carried out by means of digital image processing techniques. A commercially available digital video camera combined with a telescopic device takes a motion picture of the target panel with known geometry, which is installed on the measurement location of a bridge. The displacement of the target is calculated based on the captured images in real-time manner using image processing techniques, which require a texture recognition algorithm, projection of the captured image, and calculation of the actual displacement using target geometry and number of pixels moved. For the purpose of verification of the presented method, a laboratory test was made using shaking table test and the measured displacement by image processing techniques was compared with the data from a contact-type sensor, a linear variable differential transformer (LVDT). The proposed method gave close results to a conventional sensor. Field tests were carried out on a bridge with steel plate girders and a bridge with steel box girders. The test results gave sufficient dynamic resolution in frequency as well as the amplitude.

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