An Automated Software System for Compliance Verification of Packaged Commodities under the Legal Metrology (Packaged Commodities) Rules, 2011, through Image and Label Analysis

Abstract

Packaged commodities sold across retail, supermarket and e-commerce channels in India are legally required to display mandatory declarations — such as net quantity, Maximum Retail Price (MRP), manufacturer details, date of packing, and consumer-care information — under the Legal Metrology (Packaged Commodities) Rules, 2011. In practice, manual verification of these declarations by enforcement officials is slow, resource-intensive and prone to oversight given the sheer volume and variety of products in the market. This paper presents the design and implementation of a software system that automates this verification process by scanning product label images and validating the extracted content against the rules. The proposed pipeline combines a lightweight scene-text detector, an OCR-based text extraction module, an NLP-based field parser, and a rule-based compliance engine, and exposes its output through a report-generation module and an enforcement dashboard. The system was evaluated on a curated set of packaged-product label images across multiple product categories and shows that automated scanning can detect missing or non-compliant declarations with substantially less time and effort than manual inspection, while producing an auditable digital record of every compliance check performed.