Mobile Food Image Recognition for Automated Recipe Discovery
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Solution Overview
Problem
There is a need for innovative approaches to discover, catalog, and share recipes and meals tailored to individual preferences and dietary needs, as well as to efficiently manage nutritional content and automate meal planning, including identifying dishes in images and suggesting restaurants serving similar food.
Innovation Solution
A system and method for sharing and analyzing food and recipe information, which includes automatically identifying dishes in images stored on a mobile device, populating a database, suggesting restaurants, estimating nutritional content, and creating shopping lists, using machine learning techniques for image analysis and user interface design.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual recipe cataloging and food information management is used, then accuracy and customization can be maintained, but time consumption and labor requirements increase significantly
Solution Approach 1:
The system enables self-service through automatic image recognition of dishes, automated nutritional content analysis, and automatic shopping list generation. Users simply upload photos of their meals, and the system automatically processes all information without manual intervention, significantly reducing time consumption while maintaining high automation levels
Solution Approach 2:
The patent replaces manual mechanical processes (reading nutrition labels, manually cataloging recipes, creating shopping lists) with automated digital systems using image recognition algorithms, natural language processing, and database queries. This substitution eliminates repetitive manual tasks while improving efficiency and accuracy
2Adaptability or versatility
If comprehensive food and recipe information is collected and analyzed, then service quality and personalization improve, but system complexity and processing requirements increase
Solution Approach 1:
The system segments the complex food information management task into separate modular components: image recognition module for dish identification, nutritional analysis module for content extraction, recipe matching module for similarity detection, and shopping list generation module. Each module handles a specific function independently, making the overall system more manageable and easier to implement despite the comprehensive scope
Solution Approach 2:
The platform achieves universality by using a single integrated system to perform multiple functions: recognizing dishes from images, analyzing nutritional content, suggesting recipes, recommending restaurants, and generating shopping lists. This multi-functional approach consolidates what would otherwise require multiple separate systems into one unified platform, improving personalization while managing complexity through functional integration
Data Source
AI summary
Disclosed herein are systems, methods, and machine readable media for implementing a service for sharing and providing information about food and recipes, and in certain embodiments, including a step of automatically identifying dishes present in photos stored on a mobile device. Automatic identification of dishes in images may be used to populate a food and recipe database, suggest restaurants serving similar food, estimate nutritional content in a user's diet, populate a shopping list, and provide other food related services.