Research on Intelligent Image Feature Extraction Technology Based on Robust Subspace Learning Method
Abstract
With the rapid development of artificial intelligence and computer vision technologies, image feature extraction plays a critical role
in areas such as pattern recognition, image classification, and object detection. Traditional feature extraction methods exhibit limitations in
robustness when dealing with complex backgrounds and noise interference. Therefore, this paper proposes an intelligent image feature extraction technique based on the Robust Subspace Learning (RSL) method to enhance the accuracy and robustness of image processing. By analyzing the basic principles of the RSL method and its application in feature extraction, and comparing experimental results, the superiority of this
technique in image processing under complex environments is validated.
in areas such as pattern recognition, image classification, and object detection. Traditional feature extraction methods exhibit limitations in
robustness when dealing with complex backgrounds and noise interference. Therefore, this paper proposes an intelligent image feature extraction technique based on the Robust Subspace Learning (RSL) method to enhance the accuracy and robustness of image processing. By analyzing the basic principles of the RSL method and its application in feature extraction, and comparing experimental results, the superiority of this
technique in image processing under complex environments is validated.
Keywords
Robust Subspace Learning; Image Feature Extraction; Intelligence; Computer Vision; Robustness
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DOI: http://dx.doi.org/10.70711/aitr.v2i5.5266
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