Image processing method and device based on task identifier, equipment and medium

By using an image processing method based on task identifiers, the problems of multi-task integration and module standardization in image processing technology are solved, realizing automatic adaptation and efficient processing in a unified image processing workflow, and improving the flexibility and efficiency of task configuration.

CN120655525BActive Publication Date: 2026-09-11PING AN TECH (SHENZHEN) CO LTD
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Patent Information

Application Number
CN202510722349.4
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-30
Publication Date
2026-09-11
Estimated Expiration
2045-05-30

AI Technical Summary

Technical Problem

Existing image processing technologies have significant shortcomings in multi-task integration, module standardization, and flexible scheduling. They lack unified model compatibility, task configurability, and process automation capabilities, resulting in complex system integration and low processing efficiency.

Method used

By using a task identifier-based image processing method, raw image data is acquired and converted into a preset format. After generating standardized image data, it is bound to the task identifier, and the corresponding perception module and core network are selected for processing. Finally, the target image data is generated, realizing the dynamic selection of modular structure and a unified image processing flow.

Benefits of technology

It enables automatic adaptation to multiple image processing tasks within a unified image processing workflow, improving task configuration flexibility and image processing efficiency, and avoiding integration and reuse issues caused by differences in model structure.

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Abstract

The application relates to the technical field of image processing, can be applied to business scenes such as financial technology and medical health, and discloses an image processing method and device based on a task identifier, equipment and a medium, which comprises the following steps: acquiring original image data and converting the original image data into a preset image format to generate standardized image data; binding the standardized image data with a task identifier to form composite image data; selecting a perception module from a task library according to the task identifier, processing the composite image data to generate first intermediate feature data; inputting the first intermediate feature data into an image processing core network to generate second intermediate feature data; and selecting an output module according to the task identifier to process the second intermediate feature data to generate target image data. Through the module selection mechanism driven by the task identifier, the application realizes automatic adaptation of various image processing tasks in a unified image processing process, and improves the task configuration flexibility and image processing efficiency.
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