EasyImage

• Barcode grading with EasyBarCode2
• Benchmarking tool in Deep Learning Studio
• Learn feature for EasyMatrixCode
• Detect damaged data matrix codes
• Grading and better decoding for EasyBarCode
• Speed improvements for EasyMatch

• A new code reader tool ECodeReader allowing to read multiple code types from a single integrated interface
• Deep Learning Studio is now available on Linux ARM-64 platforms
• Neural Network “engines” allow additional devices support (OpenVINO, Tensor RT) and increased speed.
• EasyBarCode2 now supports learning from images to improve its capabilities on similar images.

• Neo is the new Licensing System of Euresys. It is reliable, state-of-the-art, and is now available to store Open eVision and eGrabber licenses.
• Neo allows you to choose where to activate your licenses, either on a Neo Dongle or in a Neo Software Container. You buy a license, you decide later.
• Neo Dongles offer a sturdy hardware and provide the flexibility to be transferred from a computer to another.
• Neo Software Containers do not need any dedicated hardware, and instead are linked to the computer on which they have been activated.
• Neo ships with its own, dedicated, Neo License Manager, which comes in two flavours: an intuitive, easy to use, Graphical User Interface and a Command Line Interface that allows for easy automation of Neo licensing procedures.

Open eVision Studio is the evaluation, prototyping and development tool of Open eVision. Its intuitive graphical user interface allows you to call and immediately see the result of any of eVision's 2D image processing functions. A scripting functionality generates the corresponding code, which can then be copied and pasted into your application.

Open eVision Studio is free (when using Open eVision 2.0 and above) and does not require any license.

Just click on DOWNLOAD OPEN EVISION STUDIO and install Open eVision. Sample images, manuals and sample programs are included.

• Flexible Masks provide a powerful way of restricting the processing to freely selected parts of the image.
• They are supported by selected image analysis functions.

• 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

• EasyImage includes operations usually performed as pre-processing steps to improve the image quality and obtain a good contrast between the background and the objects to be inspected.
• EasyImage supports gray-level and color images. Selected morphology functions are also optimized for binary (1-bit per pixel) and bi-level images.
• EasyImage includes numerous image processing functions, such as enhancement and restoration by linear or non-linear filtering, arithmetic and logic operations, geometric transformations for image registration, histogram analysis for thresholding, projection, ...

• Gain / Offset change: Normalization, Uniformization, Lookup table mapping
• Thresholding: Automatic thresholding, Min residue, max entropy, isodata, Manual thresholding; Single threshold (absolute and relative), Double threshold, Histogram-based threshold
• Arithmetic operations: Addition, Subtraction, Multiplication, Division, Copy, Invert, Module, Shift
• HDR (High Dynamic Range) image fusion
• Logical and bitwise operations: AND, OR, XOR, NOT
• Pixel comparison, Minimum, maximum
• Histogram equalization
• Linear filtering: Edge detection (Laplacian, Gradient, Prewitt, Sobel, Roberts filters), Sharpening, Smoothing (Gaussian and uniform filters). Custom kernel filtering: Kernel creation and management functions.
• Non-linear filtering: Morphological operators (Erosion, Dilation, Opening, Closing, Thinning, Thickening, Top-hat filter, Hit-and-miss transform, Morphological distance), Median filter
• Geometric transformations: Image registration (alignment), Horizontal and vertical mirroring, Translation, scaling and rotation with optional interpolation, LUT-based (un)warping
• Vector operations, Projection, Profile sampling (line segment, path, contour) and analysis
• Statistics: Measurement of Area, Binary moments, Weighted moments, Gravity center, Pixel count and pixel statistics, Minimum and maximum gray-level value, Average, variance and standard deviation
• Histogram computation and analysis
• Image focusing
• Noise estimation and reduction: Spatial noise reduction (Convolution, Median filters), Temporal noise reduction (Recursive average, Moving average, Average), Noise estimation (Root-mean-square noise, Signal-to-noise ratio)
• Elimination of the interlaced images artifacts by rebuilding or re-aligning fields
• Feature point detectors: Harris corner detector, Canny edge detector
• Other operations: Overlay, Scalar gradient