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https://github.com/prodev717/non-invasive-anemia-detection

Comparative Study of Non-Invasive Anemia Detection: RGB Analysis of Anterior Conjunctiva versus CIELAB Features from Palm Images using Artificial Neural Networks
https://github.com/prodev717/non-invasive-anemia-detection

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Comparative Study of Non-Invasive Anemia Detection: RGB Analysis of Anterior Conjunctiva versus CIELAB Features from Palm Images using Artificial Neural Networks

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# Comparative Study of Non-Invasive Anemia Detection: RGB Analysis of Anterior Conjunctiva versus CIELAB Features from Palm Images using Artificial Neural Networks

This project presents a comparative study of two non-invasive anemia detection approaches using image processing and Artificial Neural Networks (ANN).

## Methods Compared

* **Anterior Conjunctiva RGB Analysis**

* Extracts mean RGB values from eye conjunctiva images.
* Uses ANN for binary anemia classification.

* **Palm Image CIELAB Analysis**

* Converts palm images to CIELAB color space.
* Uses mean L*, a*, and b* values as features.
* Uses the same ANN architecture for fair comparison.

## Results

| Method | Accuracy |
| --------------- | -------- |
| Conjunctiva RGB | 81% |
| Palm CIELAB | 93% |

The palm-based CIELAB approach achieved better performance and showed greater robustness for non-invasive anemia screening.

## Authors

Ganesh M, Manjiswari J, Komali Priya P, Saladi Saritha, Yepuganti Karuna

## Paper

The complete research paper is available in this repository.