Advanced surface inspection for battery, paper, film or glass industries
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10/21/2024 Datasheet Advanced surface inspection for battery, paper, film or glass industries
Main benefitsOther benefitsSpecificationsSoftware
Image processing
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EasySpotDetector uses local segmentation to extract salient objects from the background. It is applicable to many materials like films, coated surfaces, steel, battery foils, glass,… Specific parameters allow to select the aspect and the size of the defect, as well as the sensitivity of the detection. The segmentation is robust to noise and doesn’t require context training or calibration.
Open eVision includes the free Deep Learning Studio application. This application assists the user during the creation of the dataset as well as the training and testing of the deep learning tool. For EasySegment, Deep Learning Studio integrates an annotation tool and can transform prediction into ground truth annotation. It also allows to graphically configure the tool to fit performance requirements. For example, after training, one can choose a tradeoff between a better defect detection rate or a better good detection rate.
Supported operating systems:
Microsoft Windows 11, 10, 8.1, 7 for x86-64 (64-bit) processor architecture
Linux for x86-64 (64-bit) and ARMv8-A (64-bit) processor architectures with a glibc version greater or equal to 2.18
Minimum requirements:
8 GB RAM
Optional NVidia GPU
Supported programming languages :
The Open eVision libraries and tools support C++, Python and the programming languages compatible with the .NET Framework (C#, VB.NET)
C++ requirements: A compiler compatible with the C++ 11 standard is required to use Open eVision
Python requirements: Python 3.11 or later is required to use the Python bindings for Open eVision
.NET requirements: .NET Framework versions 2.0 to 4.8 are supported
Supported Integrated Development Environments:
Microsoft Visual Studio 2017 (C++, C#, VB .NET, C++/CLI)
Microsoft Visual Studio 2019 (C++, C#, VB .NET, C++/CLI)
Microsoft Visual Studio 2022 (C++, C#, VB .NET, C++/CLI)
QtCreator 4.15 with Qt 5.12
Image source:
Any 8-bit grey scale image, no size limit
Region of interest:
Explicit or automatic selection of the region of interest (an oriented rectangle is fitted to the part’s edges)
A list of detected spots with their type (particle or scratch), position and size, strength, and pixel level segmentation map
Optionally, if a deep learning classifier is loaded, a class and a probability is set for each spot. The deep learning classifier is a trained EasyClassify tool.
Display functions are provided to draw the spot bounding boxes and segmented pixel
Processing speed on single core Intel i7-10850H:
Particle detection only: 200 MPixels/s
Particle and scratch: 60 MPixels/s
Minimum defect size:
2x2 pixels
No maximum defect size
PC4190 Open EasySpotDetector for USB dongle
PC4340 Open eVision EasySpotDetector
PC6512 eVision/Open eVision USB Dongle (empty)
PC6513 eVision/Open eVision Parallel Dongle (empty)
PC6514 Neo USB Dongle (empty)
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