Performance Comparison of Image Processing Techniques on Various Filters

2021 ◽  
Vol 13 (3) ◽  
pp. 34-42
Author(s):  
Shweta Singh ◽  
Ayush Sharma ◽  
Alankrita Aggarwal
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Spatial Data ◽  
Real Life ◽  
Vital Role ◽  
Performance Comparison ◽  
Spatial Data Analysis ◽  
Efficient Performance ◽  
Processing Techniques ◽  
Filtering Techniques

Image processing plays a crucial role in a large number of applications including fields of medical, watermarking in images, spatial data analysis applications. When images are static, generally, users can get good performance, though processing of real-time images are dependent on various parameters like efficacy of algorithm and filtering techniques. Researchers have observed high variation in performance during processing of real-life images; therefore, efficient filtering techniques play a vital role in determining the implemented processing algorithm's performance as well as the quality of captured images taken into consideration. Thus, the focus of this study is to discuss various widely used filtering techniques and efficient performance analysis in outdoor environmental scenarios. A real-time efficiency system is made to conclude each filter type's effectiveness in different environmental conditions with comparison and evaluation, highlighting merits and demerits of different algorithms based on application needs along with external factors.

scholarly journals Performance Improvement of Electro Optic Search and Track System for Maritime Surveillance

2020 ◽  
Vol 70 (1) ◽  
pp. 66-71 ◽  
Author(s):  
Manvendra Singh ◽  
Sudhir Khare ◽  
Brajesh Kumar Kaushik
Keyword(s):  
Real Time ◽  
Marine Environment ◽  
Selection Criterion ◽  
Vital Role ◽  
Maritime Surveillance ◽  
Detection And Tracking ◽  
Track System ◽  
Electro Optic ◽  
Video Processor ◽  
Processing Techniques

Surveillance of maritime domain is absolutely vital to ensure an appropriate response against any adverse situation relating to maritime safety or security. Electro-optic search and track (EOST) system plays a vital role by providing independent search and track of potential targets in marine environment. EOST provides real-time images of objects with details, required to neutralise threats. At long range, detection and tracking capability of EOST degrades due to uncertainty in target signatures under cluttered scenario. Image quality can be improved by using suitable sensors and enhancement using the target/background signature knowledge. Robust tracking of object can be achieved by optimising the performance parameters of tracker. In the present work, improvement in the performance of EOST subsystems such as sensor, video processor and video tracker are discussed. To improve EOST performance in terms of detection and tracking, sensor selection criterion and various real time image processing techniques and their selection criteria for maritime applications have been also discussed. Resultant improvement in the quality of image recorded under marine environment has been presented.

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.

Art as a Living System: Interactive Computer Artworks

Leonardo ◽  
1999 ◽  
Vol 32 (3) ◽  
pp. 165-173 ◽  
Author(s):  
Christa Sommerer ◽  
Laurent Mignonneau
Keyword(s):  
Image Processing ◽  
Human Computer Interaction ◽  
Real Time ◽  
Artificial Life ◽  
Real Life ◽  
Living System ◽  
Living Systems ◽  
Time Interaction ◽  
The Individual ◽  
Interactive Installations

The authors design computer installations that integrate artificial life and real life by means of human-computer interaction. While exploring real-time interaction and evolutionary image processes, visitors to their interactive installations become essential parts of the systems by transferring the individual behaviors, emotions and personalities to the works' image processing. Images in these installations are not static, pre-fixed or predictable, but “living systems” themselves, representing minute changes in the viewers' interactions with the installations' evolutionary image processes.

scholarly journals Lungs Cancer Detection Using Digital Image Processing Techniques: A Review

2019 ◽  
Vol 38 (2) ◽  
pp. 351-360 ◽  
Author(s):  
Mati ullah ◽  
Mehwish Bari ◽  
Adeel Ahmed ◽  
Sajid Naveed
Keyword(s):  
Lung Cancer ◽  
Image Processing ◽  
Computer Vision ◽  
Cancer Detection ◽  
Medical Image ◽  
Vital Role ◽  
Classification Methods ◽  
The People ◽  
Medical Diagnostic ◽  
Processing Techniques

From last decade, lung cancer become sign of fear among the people all over the world. As a result, many countries generate funds and give invitation to many scholars to overcome on this disease. Many researchers proposed many solutions and challenges of different phases of computer aided system to detect the lung cancer in early stages and give the facts about the lung cancer. CV (Computer Vision) play vital role to prevent lung cancer. Since image processing is necessary for computer vision, further in medical image processing there are many technical steps which are necessary to improve the performance of medical diagnostic machines. Without such steps programmer is unable to achieve accuracy given by another author using specific algorithm or technique. In this paper we highlight such steps which are used by many author in pre-processing, segmentation and classification methods of lung cancer area detection. If pre-processing and segmentation process have some ambiguity than ultimately it effects on classification process. We discuss such factors briefly so that new researchers can easily understand the situation to work further in which direction.

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.

scholarly journals Improved real-time data anomaly detection using context classification

2011 ◽  
Vol 13 (3) ◽  
pp. 307-323 ◽  
Author(s):  
Nemanja Branisavljević ◽  
Zoran Kapelan ◽  
Dušan Prodanović
Keyword(s):  
Anomaly Detection ◽  
Data Acquisition ◽  
Real Time ◽  
Water Distribution ◽  
Real Life ◽  
Detection Methods ◽  
Time Data ◽  
Detection Techniques ◽  
Real Time Data ◽  
Processing Techniques

The number of automated measuring and reporting systems used in water distribution and sewer systems is dramatically increasing and, as a consequence, so is the volume of data acquired. Since real-time data is likely to contain a certain amount of anomalous values and data acquisition equipment is not perfect, it is essential to equip the SCADA (Supervisory Control and Data Acquisition) system with automatic procedures that can detect the related problems and assist the user in monitoring and managing the incoming data. A number of different anomaly detection techniques and methods exist and can be used with varying success. To improve the performance, these methods must be fine tuned according to crucial aspects of the process monitored and the contexts in which the data are classified. The aim of this paper is to explore if the data context classification and pre-processing techniques can be used to improve the anomaly detection methods, especially in fully automated systems. The methodology developed is tested on sets of real-life data, using different standard and experimental anomaly detection procedures including statistical, model-based and data-mining approaches. The results obtained clearly demonstrate the effectiveness of the suggested anomaly detection methodology.

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