Image Organization via Sparse Array Classification
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Solution Overview
Problem
The challenge lies in effectively organizing and retrieving large numbers of digital images, as users often struggle to locate specific pictures due to the difficulty in remembering where they are stored across various devices and folders.
Innovation Solution
A system and method that involve receiving images and associated incidental information, organizing them into a sparse array or data structure, classifying the images using a classifier, and storing them in a database, allowing for efficient search and retrieval based on comparison with search queries, with the ability to gather and update incidental information over time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If images are stored in various file folders on devices, then users can save images, but users struggle to locate specific pictures due to difficulty in remembering storage locations
Solution Approach 1:
The system automatically extracts incidental information from images and organizes them without requiring user intervention. The image processing system autonomously performs classification, tagging, and organization tasks that would otherwise require manual user input and memory, enabling the system to serve itself in organizing the image library.
Solution Approach 2:
The patent replaces the mechanical human memory and manual filing system with an automated computer-based information extraction and organization system. Instead of relying on users to remember and manually sort images, the system uses algorithms to automatically extract metadata, classify images, and organize them in a database, substituting human cognitive functions with computational processes.
2Productivity
If users manually organize images in folders, then images can be structured, but the process is time-consuming and inefficient
Solution Approach 1:
The system performs preliminary extraction and organization of image information automatically when images are imported or uploaded. By pre-processing images to extract incidental information, classify them, and organize them into the database before the user needs to access them, the system eliminates the need for manual sorting later, saving significant time and improving productivity.
Solution Approach 2:
The image processing system autonomously performs classification, tagging, and organization tasks without requiring user intervention. The system serves itself by automatically extracting metadata, determining image categories, and placing images in appropriate locations in the database, eliminating the need for manual user sorting and significantly increasing organization speed.
3Measurement precision
If the system stores only basic image data, then storage requirements are minimal, but search accuracy and retrieval effectiveness are reduced
Solution Approach 1:
The system extracts incidental information from images by analyzing various data sources such as EXIF metadata, image content, location data, time stamps, and associated audio files. By taking out and extracting these relevant features from the raw image data, the system creates a condensed representation that improves search accuracy without requiring storage of the entire original image data, thus balancing precision with data quantity.
Solution Approach 2:
The patent introduces an intermediary layer of processed and indexed data between the raw image files and the search query. This intermediary representation includes extracted features, tags, and metadata that serve as a bridge for matching user queries with relevant images, improving search accuracy while requiring significantly less storage space than the original image data.
Data Source
AI summary
Disclosed are a system, method and computer-readable medium for organizing images. A method aspect relates to receiving an image into a device, receiving incidental information associated with the image, organizing the image and the incidental information into a data structure such as a sparse array, classifying the received image with an image classifier and storing the classified image in an image database, receiving a search query and responding to the search query by searching for and retrieving matching images in the image database based on a comparison of the image search query to the data structure.