Abstract: Disclosed are various examples for dynamically generating restriction profiles for updated software platforms. A management system can determine that updated restrictions and/or settings are included in an updated or new version of a definition file. The updated settings identified and categorized according to risk for a given enterprise group without administrator input. An updated restriction profile can be generated according to the updated settings and distributed to managed devices.

Abstract: A system and method for three dimensional (3D) vision inspection using a 3D vision system. The system and method comprising acquiring at least one 3D image of a 3D object using the 3D vision system, using the 3D vision system; extracting a 3D visible runtime mask of the 3D image; using the 3D vision system, comparing the 3D runtime visible mask to a 3D reference visible mask; and, using the 3D vision system, determining if a difference of pixels exists between the 3D runtime visible mask and the 3D reference visible mask.

Abstract: Disclosed are various examples for dynamically generating restriction profiles for updated software platforms. A management system can determine that updated restrictions and/or settings are included in an updated or new version of a definition file. The updated settings identified and categorized according to risk for a given enterprise group without administrator input. An updated restriction profile can be generated according to the updated settings and distributed to managed devices.

Abstract: Disclosed are various examples for dynamically generating restriction profiles for updated software platforms. A management system can determine that updated restrictions and/or settings are included in an updated or new version of a definition file. The updated settings identified and categorized according to risk for a given enterprise group without administrator input. An updated restriction profile can be generated according to the updated settings and distributed to managed devices.

Abstract: A system and method for training a bead detection system can include identifying a starting region on a bead based on a starting indicator. The bead can be analyzed at the starting region to identify bead characteristics. The bead can then be analyzed away from the starting region, based on the identified bead characteristics, to identify a bead profile for use during non-training bead inspection.

Abstract: Disclosed are various examples for dynamically generating restriction profiles for updated software platforms. A management system can determine that updated restrictions and/or settings are included in an updated or new version of a definition file. The updated settings identified and categorized according to risk for a given enterprise group without administrator input. An updated restriction profile can be generated according to the updated settings and distributed to managed devices.

Abstract: A system and method for training a bead detection system can include identifying a starting region on a bead based on a starting indicator. The bead can be analyzed at the starting region to identify bead characteristics. The bead can then be analyzed away from the starting region, based on the identified bead characteristics, to identify a bead profile for use during non-training bead inspection.

Abstract: A system and method for training a bead detection system can include identifying a starting region on a bead based on a starting indicator. The bead can be analyzed at the starting region to identify bead characteristics. The bead can then be analyzed away from the starting region, based on the identified bead characteristics, to identify a bead profile for use during non-training bead inspection.

Abstract: A system and method for three dimensional (3D) vision inspection using a 3D vision system. The system and method comprising acquiring at least one 3D image of a 3D object using the 3D vision system, using the 3D vision system; extracting a 3D visible runtime mask of the 3D image; using the 3D vision system, comparing the 3D runtime visible mask to a 3D reference visible mask; and, using the 3D vision system, determining if a difference of pixels exists between the 3D runtime visible mask and the 3D reference visible mask.

Abstract: A computer-implemented method for selecting at least one segmentation parameter for optical character recognition is provided. The method can include receiving an image having a character string that includes one or more characters. The method can also include receiving a character string identifying each of the one or more characters. The method can also include automatically generating at least one segmentation parameter. The method can also include performing segmentation on the image having the character string using the at least one segmentation parameter. The method can also include determining if a resultant segmentation satisfies one or more criteria and if the resultant segmentation satisfies the one or more criteria, selecting the at least one segmentation parameter.

Abstract: A computer-implemented method for selecting at least one segmentation parameter for optical character recognition is provided. The method can include receiving an image having a character string that includes one or more characters. The method can also include receiving a character string identifying each of the one or more characters. The method can also include automatically generating at least one segmentation parameter. The method can also include performing segmentation on the image having the character string using the at least one segmentation parameter. The method can also include determining if a resultant segmentation satisfies one or more criteria and if the resultant segmentation satisfies the one or more criteria, selecting the at least one segmentation parameter.

Abstract: A computer-implemented method for selecting at least one segmentation parameter for optical character recognition is provided. The method can include receiving an image having a character string that includes one or more characters. The method can also include receiving a character string identifying each of the one or more characters. The method can also include automatically generating at least one segmentation parameter. The method can also include performing segmentation on the image having the character string using the at least one segmentation parameter. The method can also include determining if a resultant segmentation satisfies one or more criteria and if the resultant segmentation satisfies the one or more criteria, selecting the at least one segmentation parameter.

Abstract: A computer-implemented method for selecting at least one segmentation parameter for optical character recognition is provided. The method can include receiving an image having a character string that includes one or more characters. The method can also include receiving a character string identifying each of the one or more characters. The method can also include automatically generating at least one segmentation parameter. The method can also include performing segmentation on the image having the character string using the at least one segmentation parameter. The method can also include determining if a resultant segmentation satisfies one or more criteria and if the resultant segmentation satisfies the one or more criteria, selecting the at least one segmentation parameter.