Image Analysis Device Metadata Filtering for Rapid Object Detection
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Solution Overview
Problem
Existing image analysis techniques are inefficient in detecting varied objects in unstructured image data across unpredictable imaging environments, requiring extensive sample collection and machine learning for each detection target, leading to high processing times.
Innovation Solution
An image analysis device generates metadata for query images, narrows down image data using this metadata, and performs object detection, allowing for rapid identification of specified objects within vast datasets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If object detection is performed on all image data using traditional machine learning methods, then detection accuracy is improved, but processing time increases significantly
Solution Approach 1:
The patent applies preliminary action by generating metadata for all image data in advance before the actual object detection process. This metadata includes pre-extracted features such as color histograms, texture information, and shape descriptors that are computed once and stored for rapid retrieval during detection operations, eliminating the need to recalculate these features for each detection query
Solution Approach 2:
The patent introduces metadata as an intermediary between the raw image data and the object detection algorithm. This metadata layer acts as a pre-processed representation that captures essential visual characteristics without containing the full complexity of the original images, enabling faster comparison and matching operations while preserving detection accuracy
2Productivity
If traditional object detection methods are used on unstructured image data, then comprehensive detection is achieved, but efficiency deteriorates
Solution Approach 1:
The patent transforms unstructured image data into structured metadata by changing the representation parameters from raw pixel values to extracted features such as color distributions, texture patterns, and shape characteristics. This parameter transformation enables efficient indexing and searching operations while maintaining the ability to handle diverse unstructured image content
3Speed
If metadata generation is performed for all image data, then search efficiency is improved, but initial processing overhead increases
Solution Approach 1:
The patent performs metadata generation as a preliminary action during image ingestion or batch processing operations. By generating metadata in advance when images are first stored in the system, the computationally intensive feature extraction is performed once during the initial processing phase, enabling rapid search operations thereafter without repeated processing overhead
Data Source
AI summary
The purpose of the present invention is to provide an image analysis technique enabling a detection subject to be rapidly detected from image data. This image analysis device generates metadata for a query image containing the detection subject, and using the metadata, narrows down the image data serving as the search subject beforehand and then conducts object detection.