Karen Jean Roberts

6424734, Jul 23, 2002

Apr 3, 1999

09/285626

Karen J. Roberts - Natick MA
Karen B. Sarachik - Newton MA

Cognex Corporation - Natick MA

G06K 900

382151, 382218

A method is disclosed for finding a pose of a geometric model of a fiducial mark within an image of a scene containing the fiducial mark. The method includes receiving input from a user including geometric model shape information and geometric model dimensions, selecting a pre-defined model having sub-models by using the model shape information, the pre-defined model being parameterized by the geometric model dimensions; and then using the pre-defined model to find an image of the fiducial mark in the image of the scene. The act of selecting a pre-defined model having sub-models includes pre-defining a model such that the sub-models and the relationships among the sub-models are selected by exploiting knowledge of features and properties of the fiducial sought so as to provide more accurate location of the fiducial. The invention provides enhanced ease of use of a sub-model-based search method by requiring only the shape and dimensions of the fiducial sought. An appropriate model and its sub-models are automatically provided.

6639624, Oct 28, 2003

Apr 11, 2000

09/547590

Ivan Bachelder - Newton MA
Karen Roberts - Natick MA
Aaron Wallack - Natick MA
William Silver - Weston MA
Edward Collins - Smithfield RI
Karen Sarachik - Newtonville MA

Cognex Corporation - Natick MA

H04N 718

348 87, 348 94, 348 95, 348126, 348129, 348130

A machine vision method for locating a leaded electronic device, such as integrated circuit chips, includes searching the image with a template depicting only a portionâe. g. , one or two âsideâ edgesâof each of one or more of the leads expected on the device. The template can include portions representing expected leads, as well as unexpected leads or unexpected lead positions. Positive and negative weightings are applied to such portions, as appropriate. A location of the device, or of one or more of its leads, is based on the results of the search.

6681039, Jan 20, 2004

Jun 3, 2002

10/160858

Karen J. Roberts - Natick MA
Karen B. Sarachik - Newton MA

Cognex Corporation - Natick MA

G06K 900

382151, 382218

A method is disclosed for finding a pose of a geometric model of a fiducial mark within an image of a scene containing the fiducial mark. The method includes receiving input from a user including geometric model shape information and geometric model dimensions, selecting a pre-defined model having sub-models by using the model shape information, the pre-defined model being parameterized by the geometric model dimensions; and then using the pre-defined model to find an image of the fiducial mark in the image of the scene. The act of selecting a pre-defined model having sub-models, includes pre-defining a model such that the sub-models and the relationships among the sub-models are selected by exploiting knowledge of features and properties of the fiducial sought so as to provide more accurate location of the fiducial. The invention provides enhanced ease of use of a sub-model-based search method by requiring only the shape and dimensions of the fiducial sought. An appropriate model and its sub-models are automatically provided.

6950548, Sep 27, 2005

Mar 16, 2001

09/809027

Ivan A. Bachelder - Newton MA, US
Yun Chang - Lexington MA, US
Yasunari Tosa - Lexington MA, US
Venkat Gopalakrishnan - Framingham MA, US
Raymond Fix - Natick MA, US
Rob Milligan - Maynard MA, US
Therese Hunt - Framingham MA, US
Karen Roberts - Natick MA, US

Cognex Corporation - Natick MA

G06K009/00

382145, 382146, 382147, 382151, 348126, 25055934, 25055937

A method and system create a geometric object model for use in machine vision inspection. A pixel image representation of an object is acquired. Based on this pixel image representation, part models for the parts of the object are generated. Each part model corresponds to a different part of the object. From the part models of the object, a model for the entire object can be created. Using this created object model, a test inspection is performed on a set of test images, and each of the test images is associated with a set of known inspection measurements. The test inspection produces a set of testing inspection measurements. If the test inspection yields satisfactory performance, the object models created are stored.