Abstract: Methods, computer software, and systems for analyzing a biological specimen (e.g., a cytological specimen) on a slide are provided. Magnified image data frames of the biological specimen are taken at different locations on the slide. An object that is not entirely contained within at least one of the image data frames is identified, and complementary portions of the object respectively located in different ones of the image data frames are matched. A fully integrated object is created from the matched object portions. Attributes of the integrated object are then analyzed.

Abstract: Methods, computer software, and systems for analyzing a biological specimen (e.g., a cytological specimen) on a slide are provided. Magnified image data frames of the biological specimen are taken at different locations on the slide. An object that is not entirely contained within at least one of the image data frames is identified, and complementary portions of the object respectively located in different ones of the image data frames are matched. A fully integrated object is created from the matched object portions. Attributes of the integrated object are then analyzed.

Abstract: Methods, computer software, and systems for analyzing a biological specimen (e.g., a cytological specimen) on a slide is provided. Magnified image data frames of the biological specimen are taken at different locations on the slide. An object that is not entirely contained within at least one of the image data frames is identified, and complementary portions of the object respectively located in different ones of the image data frames are matched. A fully integrated object is created from the matched object portions. Attributes of the integrated object are then analyzed.

Abstract: Methods, computer software, and systems for analyzing a biological specimen (e.g., a cytological specimen) on a slide is provided. Magnified image data frames of the biological specimen are taken at different locations on the slide. An object that is not entirely contained within at least one of the image data frames is identified, and complementary portions of the object respectively located in different ones of the image data frames are matched. A fully integrated object is created from the matched object portions. Attributes of the integrated object are then analyzed.

Abstract: A system and method for object inspection incorporates a level of hierarchy so that a single, primary alignment may be performed to generate a pose for multiple inspection regions. As a result, a Training mode may include the specification of a single alignment model window and a list of associated inspection region windows. Similarly, a Run-time Inspection Mode may also include specification of a single alignment model window and a list of associated inspection region windows. Such an implementation addresses the long standing problems associated with performing one or more types of inspection operations in one or more regions of a given sample-object image. By virtue of the hierarchical structure, operation of multiple inspection tools may be performed simultaneously or in any order and inspection of multiple inspection regions may be performed simultaneously or in any order.

Abstract: Methods and apparatuses are disclosed for refining groupings of edge points that represent contours in an image. The methods and apparatuses decrease data dispersion and data quantization effects. The methods and apparatuses are particularly useful for accurate and robust detection of straight line-segment features contained in noisy, cluttered imagery occurring in industrial machine vision applications. Additionally, a measurement criterion of the quality of the detected line segments is introduced.

Abstract: An efficient and reliable method and apparatus is disclosed that finds a reference point of an object profile within an image when the object is of an unknown size. The object profile is modeled using a synthetic labeled-projection model, which in conjunction with the image, is projected over a portion of the image of the object profile to derive a histogram. The histogram is normalized and a maximum of a first derivative of the histogram is defined for that position. The position of the labeled-projection model is moved relative to the image, and the process is repeated until a selected portion of the image has been examined. The first derivative of the normalized labeled projection is greatest when a feature of the image and the feature denoted by a specific synthetic label of the labeled-projection model are aligned. The method and apparatus can locate the center of the object with reliability, because use of the labeled-projection model and the histogram minimizes the * effects of image artifacts.

Abstract: A machine vision inspection system and method that increase the resolution of object image-data without physically manipulating the physical optics of cameras used during inspection. The exemplary embodiment of the invention provides a system and method that perform what may be characterized as a digital zoom. Using this digital zoom, the resolution of object image-data provided by a camera may be artificially increased. Moreover, in accordance with the exemplary embodiment of the invention, a determination may be made regarding whether portions of the object image-data are under-resolved, and based on that determination, a local digital zoom may be performed on that under-resolved portion of object image-data to increase the resolution of that portion of object image-data.

Abstract: Methods and apparatuses are disclosed for refining groupings of edge points that represent contours in an image. The methods and apparatuses decrease data dispersion and data quantization effects. The methods and apparatuses are particularly useful for accurate and robust detection of straight line-segment features contained in noisy, cluttered imagery occurring in industrial machine vision applications. Additionally, a measurement criterion of the quality of the detected line segments is introduced.

Abstract: Methods and apparatuses are disclosed for defining a locus of viable points on an elongated object, such as a locus of viable bond points on a lead of a lead frame. The locus guides the bond point positioning of a wire bonder so that the number of unacceptable wire bonds is reduced. The locus is a region adapted to receive a bond, and is defined such that for any bond centered therein, the probability of forming an unacceptable bond is reduced by offsetting the locus from at least a portion of the lead edge(s) by a minimum-offset distance. The minimum-offset distance is based on various factor(s), such as user tolerance and bond width. Further, the definition of the locus is independent of lead shape, and consequently works with a variety of lead shapes. The locus can also have various shapes for a single lead, and the shapes can vary depending on the application.

Abstract: An efficient and reliable method and apparatus is disclosed that finds a reference point of an object profile within an image when the object is of an unknown size. The object profile is modeled using a synthetic labeled-projection model, which in conjunction with the image, is projected over a portion of the image of the object profile to derive a histogram. The histogram is normalized and a maximum of a first derivative of the histogram is defined for that position. The position of the labeled-projection model is moved relative to the image, and the process is repeated until a selected portion of the image has been examined. The first derivative of the normalized labeled projection is greatest when a feature of the image and the feature denoted by a specific synthetic label of the labeled-projection model are aligned. The method and apparatus can locate the center of the object with reliability, because use of the labeled-projection model and the histogram minimizes the * effects of image artifacts.

Abstract: A system and method for filtering edge points in an edge image represented by an array of edge image coordinates each having an edge point magnitude. An edge map array is formed of edge map coordinates each assigned one of three edge indicator values indicative of the relationship between the corresponding edge image coordinate edge point magnitude and two preselected edge magnitude thresholds. An output edge point array is formed of output edge point coordinates to indicate those edge image coordinates and corresponding object image pixels that are validated by the system as being associated with likely object edge points. This is accomplished by constructing a first address stack to track memory addresses at which edge map coordinate values are stored and constructing a second address stack to track memory addresses at which output edge point coordinate values are stored as the output edge point array is constructed.