Microscope Auto-Focus via Cumulative Focal Distance Estimation
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Solution Overview
Problem
Existing imaging systems face challenges in quickly acquiring properly focused images, especially when dealing with objects or substrates that have local variations in surface irregularities, as they require time-consuming full focus searches at each location, which is not feasible in many applications.
Innovation Solution
The system employs automated and efficient focusing methods by estimating the focal distance at each new location based on focus data from previously imaged areas, progressively reducing estimation errors through cumulative averaging, allowing for fast and accurate auto-focusing across multiple locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images are acquired at different focal distances to determine the best focused image, then image focusing accuracy is improved, but imaging time increases significantly
Solution Approach 1:
The system performs preliminary action by acquiring images at multiple focal distances only at selected representative locations rather than at every imaging location. The focal distances determined at these preliminary locations are then used to guide subsequent imaging, eliminating the need for time-consuming multiple-image acquisition at every position while maintaining focusing accuracy.
Solution Approach 2:
The imaging field is segmented into multiple discrete locations where focus determination is performed. Instead of treating the entire field uniformly, the system divides it into specific sampling points where detailed focus measurement occurs, and uses interpolation or propagation to determine focus at intermediate positions, reducing overall measurement time while preserving accuracy.
2Measurement precision
If full focus search is performed at each location to account for local surface variations, then focusing accuracy for irregular surfaces is improved, but imaging speed deteriorates
Solution Approach 1:
The system applies partial action by performing complete focus searches only at a subset of locations rather than at every position. At locations where the surface is relatively uniform, partial focus determination based on neighboring measurements is sufficient. This selective approach maintains accuracy where needed while improving speed in regions where full search would be redundant.
Solution Approach 2:
The system uses feedback from focus measurements at previously visited locations to inform and optimize focus determination at subsequent locations. By continuously updating the focal distance estimates based on accumulated data from previous measurements, the system adapts to local surface variations dynamically, maintaining accuracy without repeatedly performing full focus searches.
3Productivity
If representative focal distance is estimated from previous locations, then imaging speed is improved, but estimation accuracy may deteriorate due to cumulative errors
Solution Approach 1:
The system implements periodic action by performing complete focus searches at regularly spaced intervals rather than continuously. These periodic full measurements serve as reference points that reset and validate the cumulative estimation process, preventing error accumulation over long imaging sequences while maintaining high speed between reference points.
Solution Approach 2:
The estimation system incorporates feedback mechanisms where each new measurement is used to update and correct previous estimates. This creates a self-correcting system where errors that accumulate over time are continuously monitored and adjusted based on new empirical data, maintaining accuracy while preserving the speed benefits of estimation-based focusing.
Data Source
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AI summary
The disclosure relates to methods and systems for automatically focusing multiple images of one or more objects on a substrate. The methods include obtaining, by a processor, a representative focal distance for a first location on the substrate based on a set of focal distances at known locations on the substrate. The methods also include acquiring, by an image acquisition device, a set of at least two images of the first location. The images are each acquired using a different focal distance at an offset from the representative focal distance. The methods further include estimating, by a processor, an ideal focal distance corresponding to the first location based on comparing a quality of focus for each of the images, and storing the estimated ideal focal distance and the first location in the set of focal distances at known locations.