Mixed Euro coin denominations with reflective surfaces and size variations used to illustrate AI coin classification challenges.

AI Coin Classification for Visually Similar Coins

Case Overview

Industry: Metal Processing

Solution: SolVision

Reflective coins with similar designs and small size differences can be difficult to classify using manual inspection or traditional vision systems. SolVision supports AI coin classification by analyzing visual patterns, apparent size, and surface characteristics to identify each coin by denomination.

The Case

Automated Coin Classification for Currency-Handling Operations

Coin inspection and classification are important parts of currency-handling operations. Coins must be identified and separated by denomination during processing.

Manual inspection becomes time-consuming when operators need to examine multiple coins. The task becomes more difficult when different denominations use similar metals, share nearly identical patterns, or differ only slightly in size.

An automated classification application can help in accounting for variations in reflectivity, oxidation, surface condition, pattern, and apparent size.

The Challenge

Distinguishing Reflective Coins with Similar Patterns and Sizes

Highly reflective coin surfaces can produce glare and inconsistent image details under inspection lighting. Oxidation and other surface changes may also affect the appearance of coins from the same denomination.

Some currencies create an additional classification challenge because several denominations use similar designs and differ only slightly in diameter. Indonesian 100, 200, and 500 rupiah coins, for example, have closely related visual patterns with limited size variation.

Traditional vision systems may struggle to distinguish these subtle differences consistently, increasing the risk of coin misclassification.

The Solution

AI Coin Classification Using SolVision Image Analysis

SolVision applies AI-based image processing to analyze coin patterns, apparent size, and surface appearance. The application can process images containing up to 50 coins and classify each coin by denomination.

The AI model is trained using coin images that account for differences in reflectivity, oxidation, size, and surface condition. This enables the model to distinguish coins made from similar materials or featuring nearly identical patterns.

The application supports bank tellers, cashiers, and other operators who need to classify multiple coins by denomination.

AI Coin Classification Function

SolVision identifies and classifies individual coins within an image by comparing their visible patterns, apparent size, and surface characteristics against the trained AI model. The application supports classification across multiple currencies and denominations.

Coin Classification
SolVision identifies a Japanese 500 yen coin by analyzing its pattern, apparent size, and surface characteristics.SolVision identifies a Spanish five-cent euro coin by analyzing its denomination pattern and visible surface characteristics.
Japanese Yen ¥500Spanish Euro €0.05

The Results

Enabled automated classification of multiple coins within a single image
Supported differentiation between visually similar coin denominations
Reduced reliance on manual coin classification

Application Video