Plant Drawing Line Pattern Matching for Accurate Symbol Detection

The patent segments the line detection task into multiple processing stages: acquiring the plant drawing image, preprocessing to extract line features, comparing extracted line patterns against a database of standard line patterns, and identifying matches. This segmentation allows each stage to be optimized independently, improving both accuracy and efficiency compared to traditional monolithic machine learning approaches.

The patent creates a database of standard line patterns that serves as a reference copy for comparison. Instead of relying solely on machine learning models to detect lines, the system extracts line patterns from the drawing, compares them against stored standard patterns, and identifies matches based on pattern similarity. This copying and comparison approach significantly improves detection accuracy.

The patent performs preliminary actions by pre-processing the plant drawing to extract line patterns before comparison, and by maintaining a database of standard line patterns in advance. This preliminary preparation reduces the complexity of the actual detection process, as the system only needs to compare extracted patterns against pre-organized standards rather than performing complex analysis during detection.

The patent introduces an intermediary comparison process between extracted line patterns and standard line patterns. Instead of directly detecting lines using complex machine learning models, the system uses pattern matching as an intermediary step, which simplifies the detection logic while improving accuracy through systematic comparison.