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Robust Localization Algorithm for Micromanipulation Targets Under Complex Interference Conditions
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AI
DOI：10.1109/TASE.2025.3631003.png)
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Abstract
En 中文
In the field of micromanipulation, accurate identification and localization of micro-targets are crucial. This article presents a robust high-precision micromanipulation targets localization and motion tracking algorithm to address the challenges posed by uneven illumination, shadows, object occlusion, and image noise in micromanipulation. The proposed method employs improved bilateral filtering and the Sobel operator for illumination correction and edge contour detection in the horizontal view, achieving identification and Z-directional localization of micro-targets. In the vertical view, the improved grayscale template and the feature point matching algorithms accurately identify micro-targets and locate manipulation points in the X/Y directions, even under occlusion and rotation. Experimental results demonstrate that the algorithm can identify and localize micro-targets with an average error less than 1 mu m and an average time of 120 ms, significantly improving the success rate, accuracy, and efficiency compared to existing methods. This article provides a novel approach for the precise automation of micromanipulation tasks.
Keywords:
Location awareness
Image edge detection
Gray-scale
Lighting
Accuracy
Microscopy
Noise
Interference
Tracking
Target tracking
Complex interference
computer vision
micromanipulation
micro targets
identification and localization
Journal
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6.4
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5.0K
Citations:
1.6W
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