Run-Length Binary Image Dilation Through Two-Stage Run Integration
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Solution Overview
Problem
Existing image processing techniques for dilating objects in run-length encoded binary images are inefficient when the dilation amount is large or when runs are discretely distributed, leading to prolonged processing times due to increased calculation requirements.
Innovation Solution
The method involves performing dilation processing in two stages: first, using a smaller first dilation amount to integrate runs, and then using a second dilation amount to achieve the target dilation, thereby reducing the number of runs and calculation complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If dilation processing is performed on run-length encoded binary image data with large dilation amount or discretely distributed runs, then the desired dilation effect is achieved, but the processing time becomes excessively long
Solution Approach 1:
The patent divides the dilation processing into two distinct stages: a first dilation processing with a smaller dilation amount to integrate runs, and a second dilation processing with a larger dilation amount to achieve the target dilation. This segmentation allows the system to handle run integration efficiently in the first stage, reducing the number of runs before performing the second dilation, thereby significantly reducing overall processing time while maintaining accuracy.
Solution Approach 2:
The first dilation processing serves as a preliminary action that integrates discretely distributed runs before the main second dilation processing. By performing this preliminary integration step, the system reduces the complexity of subsequent processing, as fewer runs need to be evaluated and compared during the second dilation stage.
2Reliability
If conventional dilation processing is used on run-length encoded data with many discretely distributed runs, then complete evaluation of run continuity is performed, but the calculation load increases significantly
Solution Approach 1:
The patent segments the dilation operation into two phases with different dilation amounts. The first phase uses a smaller dilation amount specifically optimized for integrating runs, which reduces the number of runs that need to be evaluated in the second phase. This segmentation decreases calculation complexity while maintaining reliable continuity evaluation through the two-stage approach.
Solution Approach 2:
The first dilation processing applies a smaller-than-target dilation amount as a partial action to achieve run integration. This partial dilation is sufficient to connect discretely distributed runs without performing the full target dilation immediately, thereby reducing the calculation load for subsequent run continuity evaluations.
3Productivity
If a single-stage dilation processing with large dilation amount is performed, then the target dilation is achieved in one step, but the number of runs to be evaluated remains high
Solution Approach 1:
The patent divides the dilation process into two stages: first dilation with a smaller amount to reduce the number of runs through integration, and second dilation with a larger amount to achieve the target dilation. This segmentation directly addresses productivity by reducing the number of runs that need to be evaluated in the second stage, thereby speeding up the overall processing.
Solution Approach 2:
The first dilation processing acts as a preliminary step that reduces the quantity of runs before the main dilation operation. By integrating runs in advance, the system decreases the number of runs that need to be processed in the second stage, improving productivity.
Data Source
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AI summary
An image processing method according to the invention is for dilating an object in a binary image represented by run-length code. The image processing method includes obtaining a target dilation amount representing how much the object is to be dilated, determining a first dilation amount decreasing as a density of runs in the image increases, comparing the target dilation amount and the first dilation amount, and performing an dilation processing based on the comparison result. If the target dilation amount is larger than the first dilation amount, a first dilation processing by the first dilation amount and a second dilation processing after the first dilation processing by a second dilation amount are performed. The second dilation amount is a difference between the target dilation amount and the first dilation amount. Otherwise, the dilation processing by the target dilation amount is directly performed.