scholarly journals The Drone Using an AI

2020 ◽  
Vol 5 (9) ◽  
pp. 1055-1057
Author(s):  
V. Subapriya ◽  
Shidhin Varghese Philip ◽  
Noufal K ◽  
Gopinath V
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Proper Time ◽  
Image Processing Techniques ◽  
Detection Algorithms ◽  
Illegal Activities ◽  
Processing Techniques

The drone which will be built is to help military , for agriculture , rooftop photography , and to keep an eye for illegal activities and to do more other cool activities . In this paper the drone which will be built is mainly used to track and monitor avenue crime and criminal activities which is totally done on proper time photograph technique plane which is managed and proposed via the use of particular methods the first processing will be implemented in real time two image processing techniques and second processing which unit will two take care the rest controll monitor and focused on two operation . Aircraft which is showen spherical place of five . Two kilometer which will mechanically feature that is to be operated and to be managed to operate. Detection algorithms have been implemented . The drone is most really useful accurate variety two title that shape to predefined database

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.

Identity Concealment When Uploading Pictures of Patients in a Tele-Medicine System

2019 ◽  
Vol 10 (2) ◽  
pp. 44-62
Author(s):  
Judith Jumig Azcarraga ◽  
John Zachary Raduban ◽  
Ma. Christine Gendrano ◽  
Arnulfo P. Azcarraga
Keyword(s):  
Image Processing ◽  
Patient Information ◽  
Medical Records ◽  
Exact Distribution ◽  
Eye Detection ◽  
Unauthorized Access ◽  
Image Processing Techniques ◽  
Detection Algorithms ◽  
Identity Concealment ◽  
Processing Techniques

Tele-medicine systems run the risk of unauthorized access to medical records, and there is greater possibility for the unlawful sharing of sensitive patient information, including children, and possibly showing their private parts. Aside from violating their right to privacy, such practices discourage patients from subjecting themselves to tele-medicine. The authors thus present an automatic identity concealment system for pictures, the way it is designed in the GetBetter tele-medicine system developed under a WHO/TDR grant. Based on open-source face- and eye-detection algorithms, identity concealment is executed by blurring the eye region of a detected face using pixel shuffling. This method is shown to be not only effective in concealing the identity of the patient, but also in preserving the exact distribution of pixel values in the image. This is useful when subsequent image processing techniques are employed, such as when identifying the type of lesions based on images of the skin.

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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