Published September 30, 2024 | Version CC-BY-NC-ND 4.0
Journal article Open

Tongue Image Diagnosis System using Machine Learning with Hand-Crafted Features

Creators

  • 1. Department of Electronics & Telecommunication, Prof Ram Meghe College of Engineering & Management New Express Way Badnera, Amravati (Maharashtra), India.

Contributors

Contact person:

  • 1. Department of Electronics & Telecommunication, Prof Ram Meghe College of Engineering & Management New Express Way Badnera, Amravati (Maharashtra), India.

Description

Abstract: Traditional Chinese Medicine theorizes a clear relationship between the visual characteristics of the tongue and the operational condition of the body's organs. The visual characteristics of the tongue can offer important indications for diagnosing diseases. Investigating tongue image processing methods for automated disease identification is a flourishing field of study in the modernization of Traditional Chinese Medicine. Although autonomous extraction of high-dimensional features is inherently more beneficial in deep learning than in conventional methods, its usefulness in medical image analysis, notably in tongue images, is restricted by the need for extensive training data. This limitation arises from the need for more labeled images. This paper demonstrated the automated diagnosis of tongue photos by analyzing digital images utilizing Image Processing techniques and using Machine Learning using major image-based features. The performance simulation and analysis of the suggested system are conducted using MATLAB Software.

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Additional details

Identifiers

DOI
10.54105/ijpmh.L1097.04060924
EISSN
2582-7588

Dates

Accepted
2024-09-15
Manuscript received on 01 September 2024 | Revised Manuscript received on 13 September 2024 | Manuscript Accepted on 15 September 2024 | Manuscript published on 30 September 2024.

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