Image Analysis Apparatus Automatic Keyword Extraction
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Solution Overview
Problem
Existing image search systems face inefficiencies in retrieving images related to input keywords, as they either require extensive face recognition or manual labor to associate words with images, and struggle with extracting keywords from images without accompanying text.
Innovation Solution
An image analysis apparatus and program that automatically determine words associated with an image by analyzing its constituent elements and scene, using a database to match features and colors with candidate keywords, thereby reducing manual labor and improving retrieval efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If face recognition or scene analysis is performed for each image to retrieve images matching input keywords, then image retrieval accuracy is improved, but processing time increases significantly
Solution Approach 1:
The patent applies preliminary action by pre-analyzing images and storing extracted features (colors, shapes, textures) and associated keywords in a database before retrieval operations. When a user searches, the system queries the pre-processed database rather than analyzing images in real-time, dramatically reducing processing time while maintaining retrieval accuracy.
Solution Approach 2:
The patent creates simplified copies of image content by extracting essential visual features (color histograms, shape descriptors, texture patterns) and storing them as searchable data structures. These feature copies enable fast database queries without requiring full image analysis during retrieval operations.
2Productivity
If manual association of words with images is performed to enable keyword-based image search, then image retrieval efficiency is improved, but labor cost increases significantly
Solution Approach 1:
The patent implements self-service by enabling the system to automatically extract visual features from images and generate associated keywords without human intervention. The automated feature extraction and keyword generation processes eliminate the need for manual image annotation, significantly reducing labor costs while maintaining retrieval efficiency.
Solution Approach 2:
The patent replaces the manual mechanical process of human operators associating words with images by implementing automated computer-based feature extraction algorithms. These algorithms analyze image content and generate keywords automatically, substituting human labor with computational processes.
3Productivity
If automatic keyword extraction from text information is performed, then keyword extraction speed is improved, but capability to extract keywords from images without text is lost
Solution Approach 1:
The patent achieves universality by creating a multi-functional system that can extract keywords from both text information and image content. The system processes different input types (text documents and images) through appropriate extraction methods, enabling it to handle diverse information sources and maintain adaptability across different scenarios.
Solution Approach 2:
The patent applies segmentation by separating the keyword extraction process into distinct pathways: one for text-based extraction and another for image-based extraction. This modular approach allows the system to apply the most appropriate method for each input type, maintaining both speed and versatility.
Data Source
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AI summary
An object of the invention is to provide an image analysis apparatus and an image analysis program storage medium storing the image analysis program that analyze an image and automatically determine words relating to the image. There are provided an acquiring section which acquires an image; an element extracting section which analyzes the content of the image acquired by the acquiring section to extract constituent elements that constitute the image; a storage section which associates and stores plural of words with each of plural of constituent elements; and a search section which searches the words stored in the storage section for a word associated with a constituent element extracted by the element extracting section.