Cover factor & open area
Optical open area, pore size distribution, and cover uniformity measured on the actual fabric.
Example outputs shown for illustration. Numbers depend on your samples and protocol.
Image: Illustrative rendering (AI-generated, gpt-image-2), not a photograph of a specific fabric
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.
% area
Open area %
Segmented area of the feature divided by the eligible area in the two-dimensional image.
Example, not a claimed result
In your report: Per-field value, size distribution, and the segmentation overlay used.
% area
Pore count
Segmented area of the feature divided by the eligible area in the two-dimensional image.
Example, not a claimed result
In your report: Per-field value, size distribution, and the segmentation overlay used.
% area
Pore size distribution
Segmented area of the feature divided by the eligible area in the two-dimensional image.
Example, not a claimed result
In your report: Per-field value, size distribution, and the segmentation overlay used.
per area
Cover uniformity map
Findings placed in sample coordinates to reveal spatial patterns and local density.
In your report: Coordinate-referenced map, regional density, and representative images.
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: Reports optical open area measured from transmitted-light images. This is a geometric measurement, not an air-permeability test; correlate it against your permeability method before using it as a substitute.
The measurement, today
Cover and openness are usually inferred from construction arithmetic or an air-permeability reading. Neither tells you where the fabric is open, or how the pores are distributed.
What it costs
Cover drives opacity, air permeability, hand, and print quality. Where a fabric is unexpectedly open, prints bleed and coatings strike through, and the fault is only found after finishing.
From image to reviewed result
- 1
Backlight the fabric
Capture a transmitted-light image so interstices read bright against the yarn.
- 2
Threshold the openings
Adaptive thresholding separates open interstices from yarn, without a fixed global cutoff.
- 3
Measure the pores
Each opening is measured for area and equivalent diameter; the distribution and median pore follow.
- 4
Map uniformity
Open area is reported per tile across the field so thin and dense regions are visible.
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
Textile pilling grade
Predict an ISO pilling grade from a fabric image, with density and the features behind the call.
Polymer film & membrane defects
Pinholes, bubbles, scratches, and coverage uniformity for films and membranes.
Particle size analysis
Static image-analysis particle sizing with shape descriptors across full fields.
Send a sample image and a measurement goal
We will show the closest ConductVision workflow and flag what needs custom validation for your images.
