Cognex Corporation

Cognex Technology and Investment Corporation

Leonid Taycher

Arman M Garakani

Juha Tapio Koljonen

The invention provides boundary-based machine vision methods and systems for comparing a pattern to an image. These contemplate the steps of finding points on a boundary in the image; identifying one or more boundary features, at least one of which is made up of multiple such points; determining point-by-point relationships, if any, between each point defining the boundary feature in the image and points on a boundary in the pattern; and determining a relationship between the boundary feature in the image and the pattern (e.g., whether the boundary feature in the image matches a corresponding feature in the pattern) as a function of the point-by-point relationships.

Machine vision methods and systems for boundary feature comparison of patterns and images

A method of training a system to identify inspection sites on a circuit board is described. The method uses a priori information, which includes a region of interest, approximate sizes and approximate spacings of a plurality of nominal pad locations, and a pad count or an aperture count. A region is created which is associated with each one of the nominal pad locations within an image of a printed circuit board. A search tool is run to find pad candidates within each one of the regions. The pad candidates are filtered. The best pad candidates are selected from among each of the found pad candidates. The best pad candidates are averaged to provide an average, and are modified based on the average.

Automatic training of inspection sites for paste inspection

A method involves training a system to identify inspection sites on a printed circuit board. The method uses a priori information, which includes a sample pad description. A training region of interest is created within an image of the printed circuit board. A search tool is run to find pad candidates within the training region. The pad candidates are filtered and false pad candidates are eliminated. The filtered pad candidates are averaged to provide an average, and are modified based on the average.

Automatic training of inspection sites for paste inspection by using sample pads

An efficient and reliable method that identifies possible reference sites in an image is disclosed. The method emphasizes customizing the identification of reference sites for each application by providing for initialization of various parameters, such as the size of the reference site. The method then uses a series of measurable parameters to filter possible reference sites in the image and produces and ordered set of possible reference sites. The highest-ranking site of the ordered set is expected to be chosen as the reference site for production. A preferred implementation is disclosed that uses multi-resolution images to enhance efficiency of the identification and that specifically measures the symmetry, orthogonality and uniqueness of the windows.

Methods for finding peaks in a characteristic surface of an image

The invention provides boundary-based machine vision methods and systems for comparing a pattern to an image. These contemplate the steps of finding boundary points in the image and comparing those points with boundary points in the pattern to identify &ldquo;matches,&rdquo; i.e., boundary points in the image that match boundary points in the pattern, &ldquo;extras,&rdquo; i.e., boundary points in the image which do not match boundary points in the pattern, and &ldquo;missing,&rdquo; i.e., boundary points in the pattern that do not match boundary points in the image. Quantitative and/or qualitative information about matching, extra or missing points can be generated, including the differences between the locations, angles and contrasts of each boundary point in the image and the corresponding boundary point in the pattern.

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Brighton, MA, United States of America

Leonid Taycher