Bringing Structure to Chaos - Template Matching for P&ID
By Anand George
Introduction: The Hidden Cost of Rework
If you’ve ever worked with vendor P&IDs, you’ve probably seen the same control valve loop, bypass line, or pump arrangement repeated across dozens — sometimes hundreds — of documents. Yet engineers continue to manually review and annotate each one as if it’s completely unique.
What if your system could recognize that structure automatically?
At Storm Consulting, we use template matching to bring order to this chaos — turning repetitive layouts into recognized, reusable patterns that speed up both annotation and validation.
What Is Template Matching?
Template matching is a computer vision technique that searches for predefined visual patterns — templates — within an image. In our case, the image is a P&ID, and the templates are commonly repeated elements such as:
- Instrument loops
- Valve-bypass arrangements
- Utility header connections
- Skid interfaces
Instead of detecting each element individually, template matching finds known blocks and assigns them meaning based on past interpretation.
How We Apply It in P&ID Workflows
Our implementation involves the following steps:
Template Library Creation - Engineers or system integrators define a small set of frequently seen blocks (e.g., from a control valve loop). These are saved as reference images.
Automated Search - When a new P&ID is processed, our tools scan it for visual matches with the template library — using OpenCV and refined matching heuristics.
Annotation Injection - Once a match is found, the tool auto-fills annotations (e.g., tag structure, expected inline instruments), which can then be validated or edited.
Iterative Refinement - New patterns encountered can be added to the library, improving future matching. The system gets smarter over time — without retraining a model.
Where It Excels
- Vendor Packages: Often structured with recurring control or instrumentation blocks
- Brownfield Projects: Many legacy drawings reuse old layouts
- P&ID Cleanups: Even when data is inconsistent, visual repetition can still be leveraged
In one case, we matched over 5,000 repeated control blocks across 120 P&IDs using just 3 templates.
What Template Matching Doesn’t Do
- It’s not a replacement for OCR or symbol detection — but a complement to them
- It works best when drawings are of reasonable quality (non-blurry, non-distorted)
- Minor shifts in layout or scaling can reduce accuracy without preprocessing
Why Not Use ML Instead?
Machine learning models require:
- Large, labeled datasets
- Time-consuming training
- Ongoing retraining for every new project
Template matching, on the other hand:
- Works out of the box with just a few examples
- Can be added on top of existing workflows
- Runs fast, locally, and is easy to update
Conclusion: Reuse What You Already Know
Engineering is full of repetition — and that’s a good thing. Template matching lets you recognize, reuse, and accelerate your work by turning repeated P&ID elements into automated building blocks.
If you’re working with vendor packages or legacy drawings, template matching can give you a massive speed-up — no AI hype needed.