Abstract: A system and method are provided for a “multi-region” autofocus video tool-type or mode within a machine vision inspection system. The user may efficiently define multiple regions of interest that are grouped as a “multi-region” set. The autofocus operations for the multi-region set are defined with a shared set of autofocus parameters. The same set of autofocus images may be used for the autofocus operations of the multi-region set. The user may conveniently also define individual autofocus regions of interest, defined with individual autofocus parameters, within the same field of view. Various user interface features allow a user to conveniently change between the individual autofocus tool-type or mode and the multi-region autofocus tool-type or mode.

Abstract: A system and method are provided for a “multi-region” autofocus video tool-type or mode within a machine vision inspection system. The user may efficiently define multiple regions of interest that are grouped as a “multi-region” set. The autofocus operations for the multi-region set are defined with a shared set of autofocus parameters. The same set of autofocus images may be used for the autofocus operations of the multi-region set. The user may conveniently also define individual autofocus regions of interest, defined with individual autofocus parameters, within the same field of view. Various user interface features allow a user to conveniently change between the individual autofocus tool-type or mode and the multi-region autofocus tool-type or mode.

Abstract: Systems and methods for identifying an interchangeable lens in a vision system having a controllable light source, a camera, and the lens to be identified. Light provided by the light source is transferred to the camera by the lens to be identified. The amount of light transferred to the camera for a particular reference configuration of the vision system depends distinguishably on the characteristics of the lens to be identified. A camera output is measured for a desired light source setting and the desired light source setting and associated measured camera output are compared with stored lens identification calibration data. The stored lens identification calibration data is obtained by measuring the camera output for a plurality of lenses using a plurality of light source settings. In various exemplary embodiments, the light transferred from the light source to the camera is reflected and/or backscattered light from the lens to be identified.

Abstract: Systems and methods that accurately detect and locate an edge or boundary position based on a number of different characteristics of the image, such as texture, intensity, color, etc. A user can invoke a boundary detection tool to perform, for example, a texture-based edge-finding operation, possibly along with a conventional intensity gradient edge-locating operation. The boundary detection tool defines a primary region of interest that will include an edge or boundary to be located within a captured image of an object. The boundary detection tool is useable to locate edges in a current object, and to quickly and robustly locate corresponding edges of similar objects in the future.

Abstract: Systems and methods for identifying an interchangeable lens in a vision system having a controllable light source, a camera, and the lens to be identified. Light provided by the light source is transferred to the camera by the lens to be identified. The amount of light transferred to the camera for a particular reference configuration of the vision system depends distinguishably on the characteristics of the lens to be identified. A camera output is measured for a desired light source setting and the desired light source setting and associated measured camera output are compared with stored lens identification calibration data. The stored lens identification calibration data is obtained by measuring the camera output for a plurality of lenses using a plurality of light source settings. In various exemplary embodiments, the light transferred from the light source to the camera is reflected and/or backscattered light from the lens to be identified.

Abstract: Systems and methods that accurately detect and locate an edge or boundary position based on a number of different characteristics of the image, such as texture, intensity, color, etc. A user can invoke a boundary detection tool to perform, for example, a texture-based edge-finding operation, possibly along with a conventional intensity gradient edge-locating operation. The boundary detection tool defines a primary region of interest that will include an edge or boundary to be located within a captured image of an object. The boundary detection tool is useable to locate edges in a current object, and to quickly and robustly locate corresponding edges of similar objects in the future.

Abstract: The lighting behavior of a vision system is inconsistent between vision systems, within a vision system over time or between parts being viewed. This inconsistency makes it difficult to correctly run part programs even within a single run of parts on a single machine. The multi area image quality tool systems, methods and graphical user interfaces adjust the light intensity of a vision system to obtain a desired image quality or characteristic of a captured image. The multi area image quality tool is used to define a plurality of regions of interest within a captured image to be used to determine the image quality or characteristic of the captured image resulting from a current illumination level. The multi area image quality tool allows a user to easily and quickly define multiple regions of interest that can be used to determine the image quality of a captured image.

Abstract: The input light settings in many vision systems often do not correspond to fixed output light intensities. The relationships between the measured output light intensity and the input light intensity are inconsistent between vision systems or within a single vision system over time. This inconsistency makes it difficult to interchange part-programs even between visions systems of one model of vision systems, because a part program with one set of light intensity values might produce images of varying brightness on another vision system. However, many measurements depend on the brightness of the image. To solve this problem, a reference lighting curve is generated for a reference vision system, relating an input light intensity value to a resulting output light intensity. A corresponding specific lighting curve is generated for a specific vision system that corresponds to the reference vision system.