Near-Field Object Detection Using Light Supplement Image Comparison
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Solution Overview
Problem
Self-walking devices face challenges in detecting near-field objects due to limited field of view and overexposure issues with existing camera systems, which can lead to collisions.
Innovation Solution
A method and apparatus utilizing a light supplement lamp to capture pre- and post-exposure images, analyzing regional bright spots to determine the presence of near-field objects by comparing pixel values and connectivity, without additional hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a front camera is used to collect obstacle information, then the walking mode of self-walking devices can be affected, but near-field objects cannot be detected due to limited field of view
Solution Approach 1:
The detection process is segmented into multiple stages: first image capture without light supplement, second image capture with light supplement, difference image generation, and connected domain analysis. This segmentation allows the system to handle different detection requirements at different processing stages, overcoming the FOV limitation by processing images in discrete analytical steps.
Solution Approach 2:
The patent transitions from spatial dimension (field of view) to temporal dimension by capturing images at different lighting conditions (before and during light supplement). This dimensional transformation allows detection of near-field objects that would be invisible or overexposed in a single static image, effectively expanding the functional detection range beyond the physical camera FOV.
2Illumination intensity
If light supplement is activated to improve visibility, then near-field objects can be illuminated, but overexposure occurs making object detection difficult
Solution Approach 1:
The system captures a first image before light supplement activation to establish a baseline of the scene without overexposure. This preliminary capture allows subsequent comparison with the second image (taken during light supplement), enabling the system to identify objects that appear only under illuminated conditions while filtering out overexposed regions through differential processing.
Solution Approach 2:
The difference image serves as an intermediary representation that bridges the two lighting conditions. By computing the pixel-wise difference between the first image (no light supplement) and second image (with light supplement), the system creates a new image where near-field objects appear as bright spots against a suppressed background, effectively mediating between the conflicting lighting conditions and enabling precise object detection.
3Measurement precision
If image processing is performed to detect near-field objects, then detection accuracy can be improved, but processing complexity increases
Solution Approach 1:
The patent extracts only the essential information needed for near-field object detection by computing the difference image and then identifying connected domains of bright spots. This extraction approach isolates the critical detection signal from the full image data, achieving high detection accuracy while keeping processing complexity manageable by focusing computational resources on the most relevant features.
Solution Approach 2:
The system creates a simplified copy of the scene through the difference image, which represents only the changes caused by light supplement activation. This copied representation contains the essential detection information in a condensed form, allowing accurate near-field object identification without processing the complete original images at full resolution and detail.
Data Source
AI summary
Disclosed are a method and apparatus for detecting a near-field object, a medium and an electronic device. In the present disclosure, the characteristics of an automatic exposure apparatus before and after light supplement of a light supplement lamp are used, two images are shot in the same direction before and after light supplement of the light supplement lamp, and whether the near-field object exists is determined through comparison of the two images. Without adding additional apparatuses, the task of discovering the near-field objects by a self-walking device is completed by using the existing apparatus, and the collision between the self-walking device and the near-field object is avoided.