Fine-Grained Texture Identification for Reliable Product Traceability

TL;DR

This paper introduces a novel product traceability method using natural texture patterns, demonstrated on Pu'er tea bricks, achieving high verification and search accuracy without traditional digital IDs.

Contribution

The study proposes a texture-based product identification system that leverages natural textures as unique identifiers, validated on a large-scale tea brick dataset.

Findings

Texture verification accuracy of 99.6%

Top-1 search accuracy of 98.9%

Feasibility of texture-based traceability demonstrated

Abstract

Texture exists in lots of the products, such as wood, beef and compression tea. These abundant and stochastic texture patterns are significantly different between any two products. Unlike the traditional digital ID tracking, in this paper, we propose a novel approach for product traceability, which directly uses the natural texture of the product itself as the unique identifier. A texture identification based traceability system for Pu'er compression tea is developed to demonstrate the feasibility of the proposed solution. With tea-brick images collected from manufactures and individual users, a large-scale dataset has been formed to evaluate the performance of tea-brick texture verification and searching algorithm. The texture similarity approach with local feature extraction and matching achieves the verification accuracy of 99.6% and the top-1 searching accuracy of 98.9%, respectively.