Image Processing Techniques and Neuro-computing Algorithms in Computer Vision

Abstract

Computer vision is a multidisciplinary field that cannot be separated with image processing techniques and Neuro-Computing specifically Deep Learning (DL) algorithms, in recent time DL techniques enable computer vision to understand the content of an image, moreover, it is working hand in hand with image processing techniques because image preprocessing are essential components in digital image analysis. Therefore, the remarkable advancement recorded by computer vision today such as in remote sensing, security, medical imaging and robotics etc. The aim of this research work was to explored the technical and theoretical contributions of image processing techniques and DL algorithms to computer vision. A systematic method of literature review was adapted. Basic image processing techniques such as standardization, denoising, filtering, and segmentation are clearly explored, concept of DL algorithms are briefly discussed, recent reviewed articles (from 2018 to date) are obtained from top journals in computer vision thus; IEEE, Elsevier and ISPR and tabulated as a major source of information for this work. We have shown some of the software's used for the implementation of deep learning researches in computer vision. Finally we concludes and give recommendations based on our findings.

Research on Lightweight Lithology Intelligent Recognition System Incorporating Attention Mechanism

“…Few researchers have utilized computer vision in deep learning [15][16][17][18] and migration learning techniques [19] to conventional domains such as geotechnical and geological engineering, etc., during the past few years. As research progresses, CV and migration learning approaches have been used for tasks such as the intelligent categorization of certain photographs of rocks.…”