A Knowledge Base Construction Method Based on Image Recognition
A construction method and image recognition technology, applied in the field of knowledge base construction based on image recognition, can solve the problems of unrealizable knowledge accumulation, low knowledge reusability, and low efficiency.
- Summary
- Abstract
- Description
- Claims
- Application Information
AI Technical Summary
Problems solved by technology
Method used
Image
Examples
Embodiment
[0033] figure 1 It is a flowchart of a method for building a knowledge base based on image recognition in the present invention.
[0034] In this example, if figure 1 Shown, a kind of knowledge base construction method based on image recognition of the present invention comprises the following steps:
[0035] S1. Obtain the target image
[0036] Obtain images containing multiple scenes and entities related to the knowledge base to be constructed, and each image contains multiple entities E 1 ,E 2 ,...,E i , ..., and each entity has multiple attribute values A 1,1 、A 1,2 ,...,A 2,1 、A 2,2 ,...,A i,j ,...;
[0037] In this embodiment, each image contains a scene such as the sky, and multiple entities such as people, objects, animals, etc., and each image needs to meet the basic definition, that is, the definition sufficient for human eyes to recognize.
[0038] S2. Target image preprocessing
[0039] First convert each image into a grayscale image, then smooth and ...
example
[0059] This embodiment builds a personnel information knowledge base based on monitoring images, which is used to assist the public security organs to quickly identify suspects, describe the suspect's movement trajectory, and help them quickly solve cases.
[0060] First, the image set collected from the case-related monitoring equipment is preprocessed according to the above method.
[0061] Second, the image is recognized using a neural network model. In this embodiment, the main task used for entity recognition is character recognition, and the attributes involved include: human body shape (fat and thin degree), clothing color, height size, which can be subdivided into: human body shape (thin, normal) , fat), clothing color (red, orange, yellow, green, blue, blue, purple), height size (less than 1.5 meters, 1.5-1.6 meters, 1.6-1.7 meters, 1.7-1.8 meters, 1.8-1.9 meters, 1.9 meters meters or more).
[0062] Finally, the coincidence degree of the pixel range of the entity a...
PUM
Abstract
Description
Claims
Application Information
- R&D Engineer
- R&D Manager
- IP Professional
- Industry Leading Data Capabilities
- Powerful AI technology
- Patent DNA Extraction
Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.
© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com