Digital Microscope Edge Detection Autofocus
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Solution Overview
Problem
Current digital microscope systems face challenges in acquiring high-quality images of samples quickly, as existing autofocusing methods are either time-consuming or compromise on accuracy, especially when samples are inclined or have varying blur levels across the imaging area.
Innovation Solution
A digital microscope apparatus and method that performs edge detection on evaluation areas of captured images, calculates blur differences between adjacent areas, and determines blurred boundaries to reimage specific areas using an appropriate autofocusing method, adjusting the imaging range and dividing areas as needed to improve focus accuracy and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If contrast AF is used to achieve high accuracy in focal point, then measurement precision is improved, but loss of time increases due to repetitive movements and evaluations
Solution Approach 1:
The patent performs preliminary actions by capturing images at multiple focal positions in advance and storing them in a lookup table. During actual operation, the system retrieves pre-captured images from the lookup table based on the desired focal position, eliminating the need for real-time repetitive movements and evaluations. This preliminary preparation resolves the contradiction by pre-computing focus data that can be quickly accessed without time-consuming search operations.
2Speed
If phase difference AF is used to achieve high speed in obtaining focal position, then speed is improved, but measurement precision deteriorates due to lowered accuracy from object size and tissue number
Solution Approach 1:
The patent segments the imaging area into multiple small areas, each with its own focus evaluation. By dividing the large field of view into smaller regions, the system can perform focused edge detection and blur evaluation on each segment independently. This segmentation allows the system to maintain high speed through parallel processing while improving precision by localizing focus assessment to specific regions rather than evaluating the entire large field at once.
Solution Approach 2:
The patent applies local quality by performing edge detection and blur evaluation specifically on evaluation areas located at boundaries between small areas. Instead of uniformly processing the entire image, the system concentrates computational resources on boundary regions where focus transitions occur. This localized approach maintains high processing speed while improving focal position accuracy through targeted analysis of critical boundary regions.
3Productivity
If the entire sample area is imaged at once, then productivity is improved, but measurement precision deteriorates due to inability to detect blurred boundaries between small areas
Solution Approach 1:
The patent segments the sample area into multiple small areas that are captured and processed independently. Each small area is captured at high speed, and then the system connects these segmented images to form the complete overview image. This segmentation enables the system to maintain high productivity through parallel capture operations while achieving precise blur detection by analyzing each segment individually and comparing boundaries between segments.
Solution Approach 2:
The patent introduces a new dimension of processing by first capturing images at a lower resolution or in a simplified format, then performing edge detection and blur evaluation on boundary regions. The system processes boundary information as a separate dimension from the main image content, allowing rapid overview generation while maintaining precise blur detection capability through specialized boundary analysis.
Data Source
AI summary
A digital microscope apparatus includes: an observation image capturing unit configured to capture an observation image of each of a plurality of small areas, an area containing a sample on a glass slide being partitioned by the plurality of small areas; and a controller configured to set at least one evaluation area for the observation image of each of the plurality of small areas, the observation image being captured by the observation image capturing unit, to perform an edge detection on the at least one evaluation area, and to calculate, using results of the edge detection on two evaluation areas that are closest between two of the observation images adjacently located in a connected image, a difference in blur evaluation amount between the two observation images, the connected image being obtained by connecting the observation images according to the partition.