• Offer Profile
  • 在过去的11年中，我们的工程师一直专注于创建专为特定应用程序设计的计算机视觉软件。在与智能视频监视以及生物识别和医疗系统有关的项目中获得的经验帮助团队开发了针对计算机视觉不同分支的解决方案所必需的所有技能。
产品介绍

  • 自适应视觉工作室2.4

  • 自适应视觉工作室2.4is an easy to use development environment for creating machine vision applications. It solves real-life tasks in many different industries and gives you freedom in the selection of hardware, including smart cameras from several manufacturers.

    这是同时发生的最好的机器视觉软件：
    • Intuitive- drag & drop development of algorithms and graphical user interfaces; instant insight into all intermediate results; clean design;
    • Powerful- loops, conditions, macrofilters and a comprehensive library of filters that are one of the fastest in the world;
    • Adaptable- support for hardware from many different vendors; C++ user filters; integrated with OpenCV.

      • 自适应视觉工作室2.4

      • How does it work?
        The application comes with a library of over 700 built-in computer vision filters. Users create programs by connecting filters with each other in an appropriate way. Various types of connections assure that any structure of data flow can be achieved, whereas hierarchical macrofilters allow for effective management of large-scale programs.

        是谁？
        自适应视觉Studio is designed to fit the needs of a wide community of machine vision engineers and researchers. People new to computer vision benefit from swift learning through interactive experimentation, whereas machine vision experts can do their job faster and in a more convenient way due to the lack of low-level programming hassle. Also C/C++ programmers with their own vision-related code bases can take advantage of the high interactiveness of Adaptive Vision Studio through easily integrated user filters.

  • 特征

    • 你可以看到一切

    • 所有编程都是通过选择过滤器并将它们相互连接来完成的。您可以将所有大脑力量集中在计算机视觉上。有关快速演示，请参阅您的第一个程序视频教程。

      该应用程序针对计算机视觉专业人员的需求进行了优化。可以查看和分析所有中间结果，从而为您提供有关算法性能的完整见解。

    • Macrofilters

    • 在不编写一行代码的情况下，您可以创建任意复杂的算法。循环和条件是通过适当的数据连接隐式创建的。转到数据流程编程以获取更多信息。

      大型程序可以组织成小的，易于理解的部分 - 大型滤镜。大型滤器是具有自己的输入，输出和数据处理周期的可重复使用的过滤器序列。

    • Hardware Acceleration

    • 有数百个现成的机器视觉过滤器。它们被组织成一个明确的类别结构，并符合清晰，一致的命名约定。它们在过滤器参考中记录。

      Filters are aggressively optimized for the SSE technology and for multicore processors. Our implementations are one of the fastest in the world (as can be seen in the Performance section).

    • 任何形状的Rois

    • You can process not only images, but also regions, paths, geometrical primitives, profiles, histograms and more. For more details see this video.

      图像处理操作可以在整个图像或任意形状区域内执行。小而精确的ROI可用于显着加速处理。

    • OPENCV支持

    • 您可以使用用户过滤器将自己的C/C ++代码与视觉编程的好处集成在一起。构建第一个用户过滤器需要30秒钟，重新编译后更新一个用户过滤器。该视频显示了它是多么简单明了。

      包括OPENCV库中的免费，开源过滤器。连同一组标准过滤器，它们可用于为简单应用程序创建极其成本效益的解决方案。

    • GigE Vision Support

    • Cameras from many different manufacturers are supported including Basler, PointGrey and XIMEA.

      自适应视觉工作室和自适应视觉GIGE SDK是Gige Vision Angimiant产品，可支持所需的一切 - 从相机配置到高性能图像获取。请参阅此视频演示。

    • 执行人库

    • Programs created in Adaptive Vision Studio can be deployed with a lightweight runtime application. A user interface (HMI) can be defined with a simple XML file (available since 2.2).

      The runtime engine is also available as a DLL library that can be used in C, C++ or C# applications.

    • HMI设计师

    • You can easily create a custom graphical user interface and thus build the entire machine vision solution using a single software package.

  • 自适应视觉Library

  • 自适应视觉库是针对工业质量检查需求进行优化的通用机器视觉工具集。图书馆的主要优势包括出色的性能和全面的机器视觉算法，并特别支持低级技术：图像处理，BLOB分析和轮廓分析。

      • 自适应视觉Library

      • 图书馆的主要部分分为六个部分，根据感兴趣的数据类型定义：
        • Image Processing- containing methods for initial image preprocessing/refinement
        • 斑点分析, Contour Analysis- two big toolsets for image analysis built upon the processing of regions (Blob Analysis) and subpixel-precise paths (Contour Analysis) extracted from an image
        • 轮廓，直方图- 用于处理和分析OD 1D数据的辅助工具集
        • 几何2D- 用于使用（可能）不同工具的对象之间执行最终测量的平台。

        Additionally, the library provides support for a number of specialised techniques like 1D Measurement, Fourier Analysis and Shape-based Template Matching.

  • Relation between Adaptive Vision Library and Adaptive Vision Studio

  • 自适应视觉库的每个功能都是自适应视觉工作室中可用的相应过滤器的基础。因此，即使人们打算使用自适应视觉库在C ++中开发最终解决方案，也可以使用自适应视觉工作室作为方便，点和点击原型制作工具。

    • 斑点分析

    • 高性能，任何形状的ROI操作，用于一元和二进制算术，图像细化，形态，平滑，空间转换，特征提取，梯度提取，大量阈值方法，圆盘IO等。

      强大的一组强大操作，用于经典的斑点分析技术。提供了多种斑点提取，设定算术，区域细化，任何内核形态，骨骼化，空间转换，特征提取，测量等等的方法。

    • 几何2D

    • Subpixel-precise工具作为设计的alternative to blob analysis, particularily suitable for shape analysis. Provides methods for contour extraction, refinement, segmentation, smoothing, classification, global transformations, feature extraction and more.

      Exhaustive toolset of geometric operations compatible with other parts of the library. Provides more than 50 operations for 2D geometry, including fitting of geometric primitives, measurements, intersections, tangents, feature extraction and more.

    • 1D测量

    • Auxillary toolsets allowing to refine and analyse 1D data extracted from the image. Innovative design of the Library puts the classic histograms and profiles far beyond their usual applications. It is not uncommon in Adaptive Vision Library to analyse the profile of distance between two paths, or histogram of the numeric features extracted from a set of objects.

      跨图像配置文件提取边缘的经典技术的一组方法。该库提供了用于测量沿任何路径的交替特性和支持测量的配对边缘的专业方法。

    • 傅立叶分析

    • 高效，健壮且易于使用的模板匹配方法。每当低级技术不足以找到所需的对象时，这些工具就会提供替代方案。

      该工具集适用于教育实验和工业应用，为频域中的傅立叶变换和图像处理提供了方法。

    • Portability

    • In the Adaptive Vision Library careful design of algorithms goes hand in hand with exhaustive hardware optimisations, resulting in performance that puts the library among the fastests in the world. Our implementations make use of SSE instructions and parallel computations on multicore processors.

      The library does not use the STL, instead being based on simple and efficient Adaptive Template Library. The latter delivers most of the STL functionality whilst avoiding the iterator abstraction and advanced template techniques. Therefore the Adaptive Vision Library can be easily ported to various embedded platforms, including ones without the full support of the C++ templates.

    • 一致性

    • 所有数据型都有自动内存管理。通过抛出适当的例外，明确处理错误。提供了创新的可选输入构建，以优雅地处理输入的特殊值。

      函数名称具有动词 +名词的形式（例如平滑图，旋转向量）。如果有几种单个操作的变体，则将其以下端开头（例如SmoothImage_Mean，SmoothImage_gauss）开始。所有结果均通过参考输出参数返回，因此始终可以进行许多输出。

  • 示例结果