Micro-STR Reader

An industry-leading Micro-STR microdot verification system, jointly developed by Nanotag Technology and DTS International Group, and protected under patent rights, can be deployed by law enforcement agencies, insurance and warranty claims investigators, microdot manufacturers, and their distributors worldwide. This breakthrough Scene Text Recognition (STR) technology allows microdots as small as 0.5mm in diameter—comparable in size to a grain of sand—to be automatically deciphered. Even microdots carrying up to 17 alphanumeric characters within a 1mm space can be decoded accurately, with the retrieved code instantly cross-checked against a secure, cloud-based owner verification database to identify the registered asset holder.

Microdots have long served as a trusted anti-theft and asset protection technology, widely adopted by vehicle manufacturers, utility providers (electricity, gas, water), and asset registries to deter illicit resale and dismantling of stolen equipment. In countries like South Africa, microdot application on vehicles is mandated by law, forming a core part of national asset tracking strategies.

With the invention of the AI-powered, patent-protected Micro-STR platform, the traditional process of using hand-held magnifiers and manually recording microdot content has been rendered obsolete. The Micro-STR Reader and mobile application now deliver automated, real-time microdot detection, decoding, and verification, even under adverse field conditions.

This system is enhanced by advanced AI-based image recognition algorithms, which employ deep learning models specifically trained on distorted, curved, low-contrast microdot images. These models ensure exceptional recognition accuracy across various surfaces—including paint, metal, glass, and plastic—and under challenging lighting conditions. Additionally, the embedded AI supports intelligent pre-processing, such as auto-focus calibration, noise suppression, character segmentation, and multi-line text alignment, enabling robust decoding of even partially damaged or degraded microdots.

The Micro-STR platform also integrates a self-learning AI module, which continuously improves performance through federated learning from field-acquired datasets—without compromising user privacy. Furthermore, the backend system leverages AI analytics to detect suspicious patterns in scan behaviors, cross-reference asset ownership histories, and assist law enforcement in mapping potential fraud or theft rings.