Email Image Classification via Facial Recognition Metadata
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Solution Overview
Problem
Current email systems lack the ability to classify attachments based on content, making it difficult and inefficient for users to access and search for specific image files within email messages.
Innovation Solution
An email server is equipped with an image classifier that automatically detects and classifies image files by comparing them with known images, using facial recognition and metadata tagging to identify and tag content, allowing for efficient searching of images within email attachments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual browsing through email messages is used to locate image files, then users can find specific images, but the process is cumbersome and time-consuming
Solution Approach 1:
The system performs preliminary classification of image attachments by automatically detecting, analyzing, and tagging images with metadata (such as content descriptions, facial recognition results, and contextual information) at the time of email receipt. This preliminary action eliminates the need for manual browsing later, as users can directly search for images based on their classified content.
Solution Approach 2:
The patent introduces an intermediary classification system that acts as a mediator between raw image attachments and user search queries. This system includes components for detecting image files, retrieving known images for comparison, comparing images to identify content, and modifying metadata - effectively bridging the gap between unstructured attachments and structured search capabilities.
2Adaptability or versatility
If typical search functions are used that only search message bodies and sender/recipient names, then search operations are simple, but content in attached files cannot be searched
Solution Approach 1:
The classification system is designed to handle multiple types of attachments beyond just images, including documents and other file types. The scanner detects various attachment types, and the system can classify and index content across different formats, making the search functionality universal and applicable to diverse attachment types while maintaining a unified approach.
Solution Approach 2:
The patent introduces an intermediary classification system that acts as a mediator between raw image attachments and user search queries. This system includes components for detecting image files, retrieving known images for comparison, comparing images to identify content, and modifying metadata - effectively bridging the gap between unstructured attachments and structured search capabilities.
3Productivity
If automatic image classification is implemented, then user access to image files is improved, but the email server requires additional processing capabilities
Solution Approach 1:
The classification system is divided into distinct functional modules: a scanner for detecting attachments, a retriever for obtaining known images, a comparator for analyzing image content, and a modifier for updating metadata. This segmentation allows the email server to progressively process images through specialized components, improving productivity while managing complexity through modular design.
Data Source
AI summary
Techniques of automatic image classification and modification in computing systems are disclosed herein. In one embodiment, a method includes scanning an inbox on email servers for emails containing image files. Upon detecting that an email in the inbox contains an image file, the method includes retrieving an identification photo of a user from a data store. The method also includes determining, via facial recognition, whether the image file in the email contains at least a partial image of the user based on the retrieved identification photo. In response to determining that the image file in the email contains at least a partial image of the user, a metadata value is inserted into the image file indicating that the image file contains at least a partial image of the user before the image file is stored in the inbox on the one or more email servers.