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Sabha, Muath
- Feature Extraction for Image Analysis And Detection Using Machine Learning Techniques
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Authors
Adel Hassan
1,
Muath Sabha
1
Affiliations
1 Faculty of Engineering and Information Technology, Arab American University, Jenin, Palestine., PS
1 Faculty of Engineering and Information Technology, Arab American University, Jenin, Palestine., PS
Source
International Journal of Advanced Networking and Applications, Vol 14, No 4 (2023), Pagination: 5499-5508Abstract
Feature extraction is the most vital step in image classification to produce high-quality and good content images for further analysis, image detection, segmentation, and object recognition. Using machine learning algorithms, profound learning like convolutional neural network CNN became necessary to train, classify, and recognize images and objects like humans. Combined feature extraction and machine learning classification to locate and identify objects on images can then be an input of automatic recognition systems ATR such as surveillance systems CCTV, to enhance these systems and reduce time and effort for object detection and recognition in images based on digital image processing techniques especially image segmentation that differentiate from computer vision approach. This article will use machine learning and deep learning algorithms to facilitate and achieve the study's objectives.Keywords
Automatic Recognition Systems, Convolution Neural Network, Digital Image Processing, Feature Extraction, Image Segmentation.Full Text
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