Abstract: This invention provides a method for contactless fingerprint detection and verification comprising illuminating a fingerprint and directing a reflected light through an imaging system using liquid crystal panels and birefringent elements to polarize the light. A plurality of polarized images are captured and used to calculate the depth of structural features on the fingertip. A means to generate a two-dimensional rolled equivalent image of the fingerprint is also provided which may then be used for verification and authentication. The invention also provides an imaging system for carrying out the method.

Abstract: This invention provides a method for contactless fingerprint detection and verification comprising illuminating a fingerprint and directing a reflected light through an imaging system using liquid crystal panels and birefringent elements to polarize the light. A plurality of polarized images are captured and used to calculate the depth of structural features on the fingertip. A means to generate a two-dimensional rolled equivalent image of the fingerprint is also provided which may then be used for verification and authentication. The invention also provides an imaging system for carrying out the method.

Abstract: The present invention includes a method of determining a location of a component on a workpiece. A before-placement standard image is acquired of an intended placement location on a standard workpiece. Then, a standard component is placed upon the standard workpiece and the placement is verified. An after-placement standard image is acquired and a standard difference image is created from the before and after standard images. Then, a before-placement test image is acquired of an intended placement location on the workpiece. A component is then placed upon the workpiece, and after-placement test image is acquired. A test difference image is created from the before and after test images. A first offset is calculated between the before standard difference image and the before test image. Then, the test difference is transformed based on the first offset to generate a difference test image (DTR) that is registered to the standard difference image.

Abstract: A pick and place machine includes a sensor disposed to acquire an image of a nozzle before a pick operation, and one or more images after the pick operation. Image analytics based upon these images reveal important characteristics that can be used to classify the pick operation. In some embodiments, a plurality of after-pick images are acquired at different poses (angular orientations).

Abstract: An electronics assembly apparatus with improved pick evaluation is provided. The apparatus includes a placement head having at least one nozzle for releasably picking up and holding a component. A robotic system is provided for generating relative movement between the placement head and a workpiece, such as a circuit board. An image acquisition system is disposed to obtain at least one before-pick image of a component pick up location and at least one after-pick image of the component pick up location. The before-pick image contains a plurality of image portions, having each image portion view the pick-up location from a different point of view, while the after-pick image contains a plurality of image portions, having each image portion view the pick-up location from a different point of view.

Abstract: An electronics assembly apparatus with improved pick evaluation is provided. The apparatus includes a placement head having at least one nozzle for releasably picking up and holding a component. A robotic system is provided for generating relative movement between the placement head and a workpiece, such as a circuit board. An image acquisition system is disposed to obtain at least one before-pick image of a component pick up location and at least one after-pick image of the component pick up location. The before-pick image contains a plurality of image portions, having each image portion view the pick-up location from a different point of view, while the after-pick image contains a plurality of image portions, having each image portion view the pick-up location from a different point of view.

Abstract: Embodiments of the present invention improve upon component level inspection performed by pick and place machines. Such improvements include inspecting the pick operation in pick and place machines by collecting images of the pick event inside the machine and identifying errors as they happen. By detecting and displaying this information as it generated on the machine, the operator or machine can take prompt and effective corrective actions.

Abstract: A pick and place machine includes a placement head configured to releasably grasp a component for placement. A robotic system is coupled to the placement head to generate relative movement between the placement head and a workpiece. An image acquisition system is configured to acquire at least one image of an intended placement location of the component before the component is placed. A controller is operably coupled to the image acquisition system, the controller is configured to process at least one before-placement image to generate a metric relative to solder deposited at the intended placement location.

Abstract: A pick and place machine includes a sensor disposed to acquire an image of a nozzle before a pick operation, and one or more images after the pick operation. Image analytics based upon these images reveal important characteristics that can be used to classify the pick operation. In some embodiments, a plurality of after-pick images are acquired at different poses (angular orientations).

Abstract: An electronics assembly apparatus with improved pick evaluation is provided. The apparatus includes a placement head having at least one nozzle for releasably picking up and holding a component. A robotic system is provided for generating relative movement between the placement head and a workpiece, such as a circuit board. An image acquisition system is disposed to obtain at least one before-pick image of a component pick up location and at least one after-pick image of the component pick up location. The before-pick image contains a plurality of image portions, having each image portion view the pick-up location from a different point of view, while the after-pick image contains a plurality of image portions, having each image portion view the pick-up location from a different point of view.

Abstract: Embodiments of the present invention improve upon component level inspection performed by pick and place machines. Such improvements include inspecting the pick operation in pick and place machines by collecting images of the pick event inside the machine and identifying errors as they happen. By detecting and displaying this information as it generated on the machine, the operator or machine can take prompt and effective corrective actions.

Abstract: The present invention includes a method of determining a location of a component on a workpiece. A before-placement standard image is acquired of an intended placement location on a standard workpiece. Then, a standard component is placed upon the standard workpiece and the placement is verified. An after-placement standard image is acquired and a standard difference image is created from the before and after standard images. Then, a before-placement test image is acquired of an intended placement location on the workpiece. A component is then placed upon the workpiece, and after-placement test image is acquired. A test difference image is created from the before and after test images. A first offset is calculated between the before standard difference image and the before test image. Then, the test difference is transformed based on the first offset to generate a difference test image (DTR) that is registered to the standard difference image.

Abstract: A system for digital image recognition which combines sparse correlation with image pyramiding to reduce the number of pixels used in correlation provides effective recognition of a reference image template without exhaustive correlation of all pixels in the reference image template. An optimal sparse pixel set is selected from the pixels of the reference image template by correlating the reference image template against a search image scene which is to be searched. Such a sparse pixel set includes those pixels which are optimal in defining the correlation sensitive features of the reference image template. By terminating the accumulation of sparse pixels at an optimal point, performance is maximized without compromising accuracy of recognition. The resultant optimal sparse pixel set is then correlated against the pixels in the search image scene through a series of transformations to find a match of the reference image template within the search image scene.