Investigation of Ways to Improve the HOG Method in the Classification of Histological Images by Machine Learning Methods

Author(s)	Farkhod, Fatto
Country	Uzbekistan
Abstract	This study analyzes ways to improve the performance of the histogram of oriented gradients (HOG) method for histological image classification using machine learning methods. We propose applying HOG to each color channel of the image, which improves the extraction of texture features characteristic of histological data. A comparative analysis of the traditional HOG and the improved approach is conducted, including an experimental evaluation of their accuracy and processing time using SVM, RF, DT, KNN, and NB classifiers. The results show that the proposed improvements improve the classification accuracy, which makes the modified HOG method promising for application in biomedical analysis.
Keywords	Features, HOG, histological images
Field	Computer Applications
Published In	Volume 6, Issue 5, September-October 2024
Published On	2024-10-30
Cite This	Investigation of Ways to Improve the HOG Method in the Classification of Histological Images by Machine Learning Methods - Farkhod, Fatto - IJFMR Volume 6, Issue 5, September-October 2024. DOI 10.36948/ijfmr.2024.v06i05.29628
DOI	https://doi.org/10.36948/ijfmr.2024.v06i05.29628
Short DOI	https://doi.org/g8p2tc

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International Journal For Multidisciplinary Research