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Date Published: 31/01/2023
Online Published: 31/01/2023
Abstract Views: 173
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DOI: https://doi.org/10.54607/hcmue.js.20.1.3614(2023)
Issue
Vol. 20 No. 1 (2023)
Section
Articles
How to Cite
Nguyễn , T. Đ., Trần , T. T. H., & Văn , T. T. (2023). IMAGE CLASSIFICATION USING KD-TREE RANDOM FOREST. HCMUE Journal of Science, 20(1), 123. https://doi.org/10.54607/hcmue.js.20.1.3614(2023)

IMAGE CLASSIFICATION USING KD-TREE RANDOM FOREST

Thị Định Nguyễn , Thị Thanh Hà Trần , Thế Thành Văn

Main Article Content

Abstract

 

 

This paper proposes a model of image classification based on a KD-Tree Random Forest structure. Each KD-Tree structure is used to classify multiple times for an input image according to the multi-layer classification model. The image classification process based on the KD-Tree Random Forest structure follows the method of building the KD-Tree Random Forest structure and training the classifier vector set. Therefore, image classification algorithms based on the KD-Tree Random Forest structure, a training set of classification vectors, and image classification models are proposed. Based on this theory, the experiment was built on the Clatech256 image set and compared with other works with the same data set to demonstrate the feasibility of the proposed method. the experimental results show that the approach is effective and can be applied to image classification systems in different fields.


 

Keywords

image classification, image classification performance, KD-Tree Random Forest, model of image classification

Article Details

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