Foreign fiber contamination
Find polypropylene, coloured, and foreign fibers in the web before they reach the dyehouse.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Results
Each measurement below comes from your own images, tied back to the annotated frame it came from, so results stay comparable across samples, locations, and conditions.
µm or count
Contaminant count
Size and shape measured for every detected object, then summarized across the population.
Example, not a claimed result
In your report: Per-object table, size distribution, and summary percentiles.
per area
Location map
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
µm or count
Fiber length & width
Size and shape measured for every detected object, then summarized across the population.
In your report: Per-object table, size distribution, and summary percentiles.
class
Colour class
Each detected feature assigned to a class using the agreed rule set, shown on the image.
In your report: Per-feature class, counts by class, and annotated overlays.
µm or count
Contamination rate per kg
Size and shape measured for every detected object, then summarized across the population.
Example, not a claimed result
In your report: Per-object table, size distribution, and summary percentiles.
Built around your image set
Use the calibrated images your team already collects, together with the locations you need to compare.
Each report includes
The artifacts your team receives, ready for review and archive.
Annotated image set
Original images with regions of interest, measurement points, masks, and finding overlays.
Measurement table
Location-indexed values, units, distributions, and QC flags in a structured export.
Method record
Calibration evidence, analysis settings, version history, and validation summary.
Confidence in every resultTraceable measurements, reviewed against your agreed reference method.
- Traceable scale
- The report records the image scale, calibration evidence, and a method-specific expanded measurement uncertainty. It does not use one product-wide accuracy number.
- Reference comparison
- The configured method is compared with your accepted reference method or reviewed annotations, and reports bias by measurement range and image condition.
- Detection performance
- Detections are evaluated against reviewed reference regions with precision, recall, and segmentation overlap, separated by the conditions that affect performance.
- Repeatability
- The locked protocol is rerun on the same inputs and on a defined repeat set. The review records variation from image acquisition, sampling, and analysis separately where possible.
What this result does not establish: Detects and locates foreign fibers visible at the imaged surface. It does not identify polymer chemistry; confirm suspect fibers by FTIR or a melt test before rejecting a bale.
The measurement, today
A stray polypropylene thread survives opening, carding, and weaving unseen. It refuses dye, then surfaces as a white streak in a finished piece. Hand inspection of a web catches the obvious ones and misses the short, pale ones.
What it costs
Contamination is usually found after dyeing, when the fabric already carries its full cost. Recycled and blended feedstock raise the odds every season, and a single contaminated lot can push a roll to seconds or scrap.
From image to reviewed result
- 1
Image the web
Capture the card web, sliver, or bale surface under controlled, even illumination.
- 2
Separate the odd fiber out
Segmentation flags fibers whose colour or reflectance departs from the base web, down to sub-millimetre fragments.
- 3
Measure and classify
Each contaminant gets a length, width, and colour class, so pale polypropylene is separated from dark trash.
- 4
Map and rate
Contaminants are mapped to their position and totalled into a contamination rate per kilogram.
Not sure this is the right measurement?
Send a representative image and your measurement goal. A ConductVision scientist will confirm whether this is the right fit, or point you to the closer workflow, before you commit to a quote.
Related applications
Fiber diameter distribution
Mean diameter, CV%, and D10/D50/D90 for wool, synthetic, and nanofiber, measured from the image.
Fiber & inclusion analysis
Count and size fibers and inclusions, with area fraction and class breakdowns.
Textile pilling grade
Predict an ISO pilling grade from a fabric image, with density and the features behind the call.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
