Embroidery Data Creation Apparatus Line Segment Connection Optimization
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Solution Overview
Problem
Conventional embroidery data creation methods face challenges in efficiently connecting line segments from image data, leading to prolonged processing times due to the need for calculating distances in a round robin manner, resulting in excessive computation and potential for useless jump stitches.
Innovation Solution
An embroidery data creation apparatus and program that preferentially searches the vicinity of a specific line segment, calculates distances between endpoint nodes, sets a search range, selects closer line segments, and sequentially connects them, reducing processing time by optimizing the search and connection process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If line segments are interconnected by calculating distances in a round robin manner, then all line segments can be connected, but processing time becomes excessively prolonged
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing distance information between line segment endpoints in a distance matrix before the main connection process. This allows the subsequent connection algorithm to access pre-computed distance data without performing expensive round robin distance calculations, thereby reducing processing time while maintaining connection completeness
Solution Approach 2:
The patent segments the line segments into groups based on color information and processes them in batches rather than handling all line segments simultaneously. This segmentation allows the system to manage computational complexity by processing smaller subsets of line segments, reducing the overall processing time while ensuring all segments are eventually connected
2Measurement precision
If all line segments are processed in a round robin manner, then comprehensive distance calculations are performed, but computational complexity increases excessively
Solution Approach 1:
The patent performs preliminary distance calculations and stores them in a structured distance matrix during an initialization phase. This pre-computation eliminates the need for repeated round robin distance calculations during the main connection process, reducing computational complexity while preserving measurement precision
Solution Approach 2:
The patent changes the parameter representation by using a distance matrix that stores pre-computed distances between all line segment endpoints. This parameter transformation converts the complex problem of repeated distance calculations into simple matrix lookups, significantly reducing computational complexity while maintaining complete distance information
3Ease of manufacture
If line segments are connected without careful interconnection, then the process is simple, but useless jump stitches occur frequently
Solution Approach 1:
The patent implements feedback mechanisms by continuously monitoring the connection process and using distance information to guide subsequent connection decisions. The system adjusts connection choices based on calculated distances and previously made connections, preventing useless jump stitches while maintaining a relatively simple overall process
Solution Approach 2:
The patent performs preliminary sorting and grouping of line segments based on color and spatial proximity before the connection process. This pre-organization ensures that line segments are connected in a logical sequence that minimizes jump stitches, achieving both simplicity and quality without requiring complex real-time decision-making
Data Source
AI summary
The process searches a block that contains a current line segment for any other line segments and, if they are found, calculates a distance between an endpoint of the current line segment and endpoint nodes of all the line segments found in the block. The process sequentially searches for the line segments in the block in accordance with search order determined on the basis of a search ranking table if a search range is not crossed over and calculates the distances between the endpoint of the current line segment and the endpoint nodes of the found line segments. Then, the process compares the distance from the endpoint node of the already line segment found and the distance from the newly found endpoint node and outputs the smaller one as the next line segment.