Transmission Line Foreign Object Detection in Foggy Inspection Images

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Solution Overview

Problem

Existing image recognition technologies for identifying foreign objects on transmission lines fail to accurately distinguish between complex background terrains and objects, leading to low accuracy in identifying foreign objects due to environmental factors like rain, fog, and snow.

Innovation Solution

A method involving a super-resolution reconstruction defogging algorithm to enhance image clarity, followed by semantic segmentation and object extraction using a segment anything model and morphological augmentation to construct a robust foreign object database for accurate identification.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If existing image recognition algorithms are used to identify foreign objects on transmission lines, then the inspection process can be automated, but the accuracy of identification is low due to complex background terrains and environmental factors

Engineering Contradiction:

Improveautomation of foreign object identificationVSAvoidaccuracy of foreign object identification

Core Design Contradiction:

Extent of automationVSMeasurement precision

Solution Approach 1:

The patent applies image segmentation to divide the transmission line image into multiple regions, separating the foreign objects from the complex background terrain. This segmentation allows the recognition system to focus on specific regions containing foreign objects, thereby improving identification accuracy while maintaining automation.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent enhances local image quality by applying super-resolution reconstruction and defogging algorithms specifically to regions containing foreign objects. This local enhancement improves the clarity and detail of foreign objects without processing the entire image, thus improving identification accuracy while maintaining computational efficiency for automated inspection.

Inventive Principle:

Principle #3Local quality

2Measurement precision

If manual inspection is used to identify foreign objects on transmission lines, then identification accuracy may be maintained, but inspection efficiency is low and missing inspections are likely to occur

Engineering Contradiction:

Improveaccuracy of foreign object identificationVSAvoidinspection efficiency

Core Design Contradiction:

Measurement precisionVSProductivity

Solution Approach 1:

The patent implements a feedback mechanism where the recognition system continuously learns from inspection results, adjusting its parameters and models to improve accuracy over time. This feedback loop enables the automated system to maintain high identification accuracy comparable to manual inspection while achieving superior inspection efficiency and consistency.

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The patent performs preliminary image processing including super-resolution reconstruction, defogging, and segmentation before foreign object recognition. These preliminary actions prepare the images in advance, enabling the automated recognition system to achieve high accuracy by preprocessing the data to eliminate environmental interference and enhance object features.

Inventive Principle:

Principle #10Preliminary action

3Measurement precision

If super-resolution reconstruction defogging algorithm is applied to process transmission line images, then image clarity is improved, but processing time increases

Engineering Contradiction:

Improveclarity of transmission line imageVSAvoidimage processing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent applies super-resolution reconstruction and defogging algorithms selectively to only those image regions containing foreign objects, rather than processing the entire image. This partial application of image enhancement techniques improves foreign object clarity while significantly reducing processing time compared to full-image processing.

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The patent segments the transmission line image to identify regions containing foreign objects, then applies computationally intensive super-resolution and defogging algorithms only to these segmented regions. This segmentation-based approach maintains image clarity improvement while minimizing overall processing time by avoiding redundant computation on background areas.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS20260011107A1Method and system for identifying foreign object on transmission line, computer device, and medium

Publication Date: 2026.01.08 SICHUAN SIJI TECHNOLOGY CO LTD

AI summary

The present disclosure discloses a method and system for identifying a foreign object on a transmission line, a computer device, and a medium, and relates to the field of image identification technologies. According to the present disclosure, an impact of an environment on a transmission line inspection image is eliminated by using the super-resolution reconstruction defogging algorithm, then the transmission line image is semantically segmented by using an image segmentation algorithm to reduce an impact of a background image on identification of the foreign object on the transmission line, and finally, the foreign object on the transmission line is quickly and accurately identified according to the transmission line foreign object sample database constructed based on a segment anything model and an object morphological augmentation algorithm.