Circular Calibration of Depth Extraction in Stereo Configuration
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 3
Abstract
Lens distortion is defined as departure from rectilinear projection of an imaging system which affects the accuracy of almost all vision applications. This work addresses the problem of distortion with investigating the effects of camera’s view angle and spherical nature of lens on image, and then derives a closed-form solution for the correction of distorted pixel's angle in image according to geometric shape of lens. We first propose technique that explores the linear relation between lens and charge-coupled device in intrinsic environment of camera, through analysis of pixel’s angle in field of view. Second technique for depth extraction through linear transformation in rectangular configuration is achieved by considering the camera’s background in field of view which provides optimal results in closed environment. As the object moves away from the center of image in image plane, depth accuracy starts to deteriorate due to radial distortion. To rectify this problem, we finally purpose circular calibration methodology which addresses this inaccuracy and accommodate radial distortion to achieve optimal results up to 98%, in great depth with very large baseline. Results show the improvement over established stereo imaging techniques in depth extraction where the presented considerations are not observed. This methodology ensures high accuracy of triangulated depth with very large base line.
Authors and Affiliations
Zulfiqar Ibrahim, Zulfiqar Ali Bangash, Muhammad Zeeshan
Keywords
Related Articles
- EP ID EP278274
- DOI 10.14569/IJACSA.2018.090336
- Views 97
- Downloads 0
A Hybrid Algorithm based on Invasive Weed Optimization and Particle Swarm Optimization for Global Optimization
In this paper, an effective combination of two Metaheuristic algorithms, namely Invasive Weed Optimization and the Particle Swarm Optimization, has been proposed. This hybridization called as HIWOPSO, consists of two mai...
EEG-Based Emotion Recognition using 3D Convolutional Neural Networks
Emotion recognition is a crucial problem in Human-Computer Interaction (HCI). Various techniques were applied to enhance the robustness of the emotion recognition systems using electroencephalogram (EEG) signals especial...
Bio-NER: Biomedical Named Entity Recognition using Rule-Based and Statistical Learners
The purpose of extracting of Bio-Medical Entities is to recognize the particular entities, whether word or phrases, from the unstructured data contained in the text. This work proposes different approaches and methods, i...
A Convolutional Neural Network for Automatic Identification and Classification of Fall Army Worm Moth
To combat the problem caused by the Fall Army Worm in the country there is a need to come up with robust early warning and monitoring systems as the current manual system is labor intensive and time consuming. The automa...
Comparison of the Information Technology Development in Slovakia and Hungary
Nowadays the role of information is increasingly important, so every company has to provide the efficient procurement, processing, storage and visualization of this special resource in hope to stay competitive. More and...