National Instruments Corporation

Accretech Usa, Inc.

Siming Lin

Dinesh R Nair

Darren R Schmidt

Kevin L Schultz

Nicolas F Vazquez

Satish Sadam

Paul Forderhase

Kevin M Crotty

Ju Jin

Michael D Robbins

Vishal Verma

Zhiyan Huang

Nicolas Vazqúez

System and method for analyzing an image. A received image, comprising an object or objects, is optionally preprocessed. Invariant shape features of the object(s) are extracted using a generalized invariant feature descriptor. The generalized invariant feature descriptor may comprise a generalized invariant feature vector comprising components corresponding to attributes of each object, e.g., related to circularity, elongation, perimeter-ratio-based convexity, area-ratio-based convexity, hole-perimeter-ratio, hole-area-ratio, and/or functions of Hu Moment 1 and/or Hu Moment 2. Non-invariant features, e.g., scale and reflection, may be extracted to form corresponding feature vectors. The object is classified by computing differences between the generalized invariant feature vector (and optionally, non-invariant feature vectors) and respective generalized invariant feature vectors corresponding to reference objects, determining a minimum difference corresponding to a closest reference object or class of reference objects of the plurality of reference objects, and outputting an indication of the closest reference object or class as the classification.

Shape feature extraction and classification

A substrate illumination and inspection system provides for illuminating and inspecting a substrate particularly the substrate edge. The system uses a light diffuser with a plurality of lights disposed at its exterior or interior for providing uniform diffuse illumination of a substrate. An optic and imaging system exterior of the light diffuser are used to inspect the plurality of surfaces of the substrate including specular surfaces. The optic can be rotated radially relative to a center point of the substrate edge to allow for focused inspection of all surfaces of the substrate edge.

Automatic wafer edge inspection and review system

A system and method for measuring the similarity of multiple-color images and for locating regions of a target image having color information that matches, at least to a degree, the color information of a template image. A color characterization method operates to characterize the colors of an image and to measure the similarity between multiple-color images. For each image pixel, the method determines a color category or bin for the respective pixel based on HSI values of the respective pixel, wherein the color category is one of a plurality of possible color categories in HSI color space. In various embodiments, the weight of the pixel may be fractionally distributed across a plurality of color categories, e.g., as determined by applying fuzzy pixel classification with a fuzzy membership function. The percentage of pixels assigned to each category is then determined. The percentage of pixels in each color category is then used as a color feature vector to represent the color information of the color image. A quantitative measurement of the color similarity between color images is then computed based on the distance between their color feature vectors. Once the color information of a template image has been characterized, a target image may be searched in order to locate regions within the target image having matching color information. In one embodiment, a coarse-to-fine heuristic may be utilized, in which multiple search stages of decreasing granularity are performed. A first-stage search may operate to identify a list of candidate match regions based on the city-block distance of the color feature vector computed using a sub-sampling scheme. These candidate match regions may then be examined in further detail in order to determine final matches.

System and method for color characterization using fuzzy pixel classification with application in color matching and color match location

A system and method for locating regions in a target image matching a template image with respect to color and pattern information. The template image is characterized with regard to pattern and color. A first-pass search is made using color information from the color characterization of the template image to find color match candidate locations preferably via a hill-climbing technique. For each color match candidate location, a luminance pattern matching search is performed, optionally using a hill-climbing technique, on a region proximal to the location, producing final match regions. For each final match region a hue plane pattern match score may be calculated using pixel samples from the interior of each pattern. A final color match score may be calculated for each final match region. A final score is calculated from luminance pattern match, color match, and possibly hue pattern match, scores, and the scores and sum output.

Locating regions in a target image using color match, luminance pattern match and hill-climbing techniques

A system and method for locating regions in a target image that match a template image with respect to color and pattern information. The method may comprise performing a first-pass search using color information obtained in a color characterization analysis of the template image in order to find a plurality of color match candidate locations. For each color match candidate location, a region proximal to the location may then be searched in detail, based on pattern information obtained in a pattern analysis of the template image.

System and method for locating color and pattern match regions in a target image

A system and method for locating regions in a target image that match a template image with respect to color and pattern information. The template image is characterized with regard to pattern and color. The method comprises performing a first-pass search using color information from the color characterization of the template image to find one or more color match candidate locations. For each color match candidate location, a luminance, i.e., gray scale, pattern matching search is performed on a region proximal to the location, producing one or more final match regions. For each final match region a hue plane pattern match score may be calculated using pixel samples from the interior of each pattern. A final color match score may be calculated for each final match region. A weighted sum of luminance pattern match, hue pattern match, and color match scores may be calculated, and the scores and sum output.

Locating regions in a target image using color matching, luminance pattern matching and hue plane pattern matching

A color characterization method operates to analyze each respective pixel of at least a subset of the pixels of an image object. The image is obtained in HSI format, or alternatively converted from another format to HSI. For each respective pixel, the method determines a color category or bin for the respective pixel based on values of the respective pixel. The color category is one a plurality of possible color categories or bins in the HSI color space. As the pixels are analyzed and assigned to color categories, the method stores information in tho computer regarding the number or percentage or pixels in each of the color categories. A color matching method uses the color characterization method. The color matching method determines similarity of colors between a template image object and a region of interest (ROI). The color matching method first performs the above color characterization technique on each of a template image object and a ROI (region of interest) and then generates match information based on the color information of the template image object and the color information of the ROI, wherein this match information indicates the similarity of colors between the template image object and the ROI.

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Austin, TX, United States of America

Siming Lin