DOI: 10.5281/zenodo.15119009
title: Count Coins Image Dataset

description: Description:

Count Coins Image Dataset have been an essential part of human civilization, serving as a medium of exchange and a symbol of value for thousands of years. Typically small, flat, and often round, coins are minted by governments or authorized entities, making them legal tender. While traditionally made from metals or alloys, some modern coins are produced using man-made materials. Coins feature intricate designs, including images, numerals, or text, which often have historical or cultural significance. The two sides of a coin are referred to as the obverse (commonly known as "heads") and the reverse ("tails"). The obverse usually displays a notable figure or symbol, while the reverse might feature a coat of arms, denomination, or other emblematic imagery.

The Count Coins Image Dataset captures the diversity of coinage from around the world, providing a valuable resource for image processing and computer vision applications. This dataset is designed to help users develop and refine algorithms for coin detection, recognition, and counting, making it particularly useful for those new to image preprocessing.

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Dataset Content

The dataset includes high-quality images of coins from various currencies, offering a comprehensive overview of global coinage. The coins included are:



US Coins: Featuring iconic American currency, including pennies, nickels, dimes, quarters, and more.

Chinese Coins: Showcasing modern and traditional coins from China, with varying designs and inscriptions.

Yen Coins: Representing Japanese currency, including the distinct Yen coins.

Euro Coins: Covering coins from multiple Eurozone countries, highlighting the diversity within the Euro currency.

Indian Rupee Coins: Displaying coins used in India, with various denominations and designs.

Peso Coins: Featuring coins from countries using the Peso, such as Mexico and the Philippines.


The images were primarily sourced through web scraping from Google Image searches. They were carefully filtered and selected based on quality to ensure that the dataset provides clear and usable images. However, some images with unique challenges were intentionally include to help users practice and enhance their preprocessing skills.

Challenges and Use Cases

This dataset is design to pose a variety of challenges, making it an excellent resource for those interest in image preprocessing and algorithm development. Key challenges include:



Shape Variability: While many coins are round, not all are, introducing a shape variation challenge.

Inconsistent Backgrounds: The images have different backgrounds, requiring effective background removal techniques.

Color Differences: The coins vary in color, depending on their material composition, adding complexity to color normalization processes.

Position Variations: Most coins are position horizontally flat, but some images include coins at different angles or partially obscured, testing the robustness of detection algorithms.

Lighting and Reflection: Variations in lighting conditions and reflections on coin surfaces present additional preprocessing hurdles.


Applications

The Count Coins Image Dataset can be utilized in various applications, including:



Coin Detection and Counting: Developing algorithms to automatically detect and count coins in images, useful in financial technology (FinTech) solutions.

Currency Recognition: Training models to recognize and categorize different types of coins, applicable in automate sorting machines and educational tools.

Image Preprocessing Practice: Offering a hands-on challenge for those learning or refining their skills in image preprocessing, including tasks like background removal, color correction, and feature extraction.

Computer Vision Research: Contributing to research in object detection and classification, particularly in domains requiring high precision and adaptability to variable conditions.


Conclusion

The Count Coins Image Dataset is a versatile and challenging collection, ideal for both beginners and advanced practitioners in the field of computer vision. By working with this dataset, users can develop robust image preprocessing techniques and gain insights into the complexities of coin detection and recognition across different global currencies.

This dataset is sourced from Kaggle.