Philippine Currency Identifier is a mobile application designed to assist users in identifying and authenticating Philippine currency.
The "Philippine Currency Identifier" is a thesis-developed app that helps visually impaired people in the Philippines identify currency denominations using a convolutional neural network. It offers vocal denomination recognition and a user-friendly interface for easy accessibility, enabling independent financial transactions through a quick smartphone scan. This app represents a significant advancement in assistive technology and inclusivity.
- Denomination Recognition: Instantly identifies and vocalizes the denomination of Philippine currency, aiding users in recognizing various banknotes and coins.
- Accessibility Optimized: Specifically designed to enhance usability for visually impaired individuals, ensuring that navigation and interaction are intuitive and straightforward.
- Real-Time Identification: Employs advanced convolutional neural network technology to deliver swift and precise currency identification, facilitating immediate feedback.
- Money Counter Tool: Includes an integrated money counter feature that assists users in calculating the total value of a batch of currency, simplifying financial transactions and money management.
- Mobile Device: A compatible mobile device with a functional camera and audio output capabilities
- Storage Memory: A minimum of 100mb of available storage.
- Android Version: Supported by Android version 7 and up to avail all the application features.
Easily download the "Philippine Currency Identifier" app by scanning a QR code. Simply point your device's camera at the QR code, and you'll be directed to the download page
If you encounter any issues with the QR code, please click here or manually visit bit.ly/ph-identifier to download the app directly
This section provides an overview of the key technologies and frameworks utilized in the development of the Philippine Currency Identifier app:
- Programming Languages: Kotlin and Python.
- Integrated Development Environments: Android Studio and Visual Studio.
- Machine Learning Frameworks: TensorFlow and Google Colab.
- Annotation and Data Preparation Tools: LabelImg, Video to Image and Label Counter tools.
- Design and Prototyping Tool: Adobe XD and Photoshop.
- Application Programming Interfaces (APIs): Google Text-To-Speech API.
If you encounter any issues or have questions about the "Philippine Currency Identifier" app, please don't hesitate to reach out to me directly at wilhelmus.olejr@gmail.com. As the sole developer, I am dedicated to offering support and will do my best to respond to your queries and concerns promptly, aiming to provide solutions and enhance your app experience.
- Thanks to Sir Odon Maravillas for being an invaluable thesis adviser, offering steadfast support, guidance, and encouragement throughout the thesis development process.
- Thanks to Sir Salimar Tahil, Sir Marvic Lines, Sir Gadmar Belamide, and Sir Theo Sanson for their critical observations and passionate guidance that significantly enhanced the quality of my thesis.
- Thanks to Sir Jaydee Ballaho, Sir Ram, Sir Edwin Arip, and Ma’am Marjorie Rojas for their insightful feedback and expertise which were instrumental in refining the application and its functionality.
- Thanks to the panelists, Sir Ceed Lorenzo and Ma’am Mara Marie Liao, for their constructive feedback during the defense, which was crucial in improving the thesis's focus and quality.
- Thanks to my friends and colleagues for their constant support, motivation, and camaraderie, which were essential during challenging times throughout the thesis process.
- Thanks to God for providing unwavering guidance and strength, inspiring perseverance and resilience throughout the journey of this academic endeavor.
We welcome contributions of all kinds from the community. If you're interested in helping improve the Philippine Currency Identifier, please:
- Fork the repository and create your branch from
main
. - Write clear code and add appropriate tests.
- Submit a pull request with comprehensive descriptions of changes.
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V1.0.0
Initial release.
Scanning errors on Android 10 and below.
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V2.0.0
Reduced app file size by removing extra ML models.
Addressed the high file size issue reported by users.
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V3.0.0
Current stable release.
Resolved Android 10 and below scanning issue.
App working effectively across all supported versions.