US 5,335,293 A · Product inspection method and apparatus

Abstract

Described herein is an automated quality inspection station for evaluating color component characteristics of a product. The inspection station includes a color video camera, for capturing video frames of product images, and a control system for analyzing those video frames. The control system is programmed to perform a reference calibration and then a sample calibration. During the reference calibration an operator identifies component type areas from a displayed reference frame of a typical product assortment. The control system calculates color value density curves from the identified areas. The density curves are then calibrated to each other by scaling each of the density curves by a scaling factor. The scaling factors can either be provided directly by the operator or default values can be calculated by the control system. Default scaling factor values are calculated by summing the product of the corresponding density curve and an overall histogram of a sample video frame over a range of color values. Individual pixels are classified as one of a plurality of component types according to the highest calibrated density curve at the pixels' color value.

Claims60

Dependent claims

An automated quality inspection device for evaluating optical component characteristics of a product, the inspection device comprising:

means for capturing video frames of product images, each video frame comprising an array of color values, each color value being specified by at least one variable;
component selection means for allowing an operator to identify portions of individual component types within a reference video frame;
control means for (1) deriving relative component type probability curves from the identified portions of the individual component types, and (2) classifying individual color values as single component types according to the highest relative component type probability for each individual color value;
wherein the control means includes processing means for deriving the relative component type probability curves by comparing color values of the identified portions of component types to the color values of an overall sample video frame.

1 more element

An automated quality inspection device for evaluating optical component characteristics of a product, the inspection device comprising:

means for capturing video frames of product images, each video frame comprising an array of color values, each color value being specified by at least one variable;
component selection means for allowing an operator to identify portions of individual component types within a reference video frame;
control means for (1) deriving relative component type probability curves from the identified portions of the individual component types, and (2) classifying individual color values as single component types according to the highest relative component type probability for each individual color value;
wherein the control means has processing means for:
compiling reference histograms of color values occurring within the identified portions of the reference video frame;
calculating color value density curves from the reference histograms;
compiling an overall histogram of color values within a sample video frame;
comparing the density curves to the overall histogram to obtain a scaling factor corresponding to each density curve;
and
scaling the density curves by the scaling factors to obtain the relative component type probability curves.

7 more elements

An automated color component classification device for identifying component types in a sample product having a plurality of component types, the inspection device comprising:

a sample surface for supporting product which is to be inspected;
a camera positioned relative to the optical inspection surface to produce video frames of the supported sample product, each video frame containing an array of pixels, wherein each pixel has an associated color value which is specified by at least two variables;
a video display monitor which displays video frames to an operator;
component selection means for allowing an operator to identify portions of individual component types within a reference video frame;
a data processor operably connected to the camera, the video display monitor, and the component selection means, the data processor being programmed to derive relative component type probability curves from the identified portions of the individual component types, and to classify individual color values as single component types according the highest relative component type probability for each color value;
wherein the data processor is further programmed to:
compile reference histograms of color values occurring within the identified portions of the reference video frame;
calculate color value density curves from the reference histograms;
and
scale the density curves by scaling factors to obtain the relative component type probability curves.

7 more elements

An automated color component classification device for identifying Component types in a sample product having a plurality of component types, the inspection device comprising:

a sample surface for supporting product which is to be inspected;
a camera positioned relative to the optical inspection surface to produce video frames of the supported sample product, each video frame containing an array of pixels, wherein each pixel has an associated color value which is specified by at least two variables;
a video display monitor which displays video frames to an operator;
component selection means for allowing an operator to identify portions of individual component types within a reference video frame;
a data processor operably connected to the camera, the video display monitor, and the component selection means, the data processor being programmed to derive relative component type probability curves from the identified portions of the individual component types, and to classify individual color values as single component types according the highest relative component type probability for each color value;
wherein the data processor is further programmed to:
compile reference histograms of color values occurring within the identified portions of the reference video frame;
calculate color value density curves from the reference histograms;
compile an overall histogram of color values within a sample video frame;
compare the density curves to the overall histogram to obtain a scaling factor corresponding to each density curve;
and
scale the density curves by the scaling factors to obtain the relative component type probability curves.

9 more elements

An automated quality inspection device for evaluating color component characteristics of a product, the inspection device comprising:

an optical transducer which produces a video signal representative of color characteristics of the product;
a frame grabber which receives the video signal and captures video frames representing images of the product, each video frame containing an array of pixels, each pixel having an associated color value which is specified by at least two variables;
a video display upon which a reference video frame is displayed to an operator;
component selection means for allowing the operator to identify portions of component type areas from the displayed reference video frame;
a data processor operably connected to read pixel color values from the frame grabber and programmed to:
(a) compile reference histograms of color values within the identified portions of the reference frame component type areas;
(b) calculate color value density curves from the reference histograms;
(c) calibrate the density curves relative to each other;
(d) classify an individual pixel as the component type having the highest calibrated density curve value at the color value of the individual pixel;
wherein the data processor is programmed to calibrate the density curves by:
compiling an overall histogram of color values within a sample video frame;
comparing the density curves to the overall histogram to obtain a density scaling factor corresponding to each density curve;
and
scaling the density curves by their corresponding density scaling factors to obtain corresponding relative probability curves which represent the probability of any single color value occurring in any single component type relative to any other component types.

11 more elements

A method of classifying video pixels in a product inspection device as one of a plurality of component types, wherein each pixel has an associated color value, each color value being specified by at least one variable, the method comprising the following steps:

capturing a reference video frame of a product image, the reference video frame comprising an array of video pixels;
identifying portions of individual component types within the reference video frame;
deriving relative component type .probability curves from the identified portions of the individual component types;
classifying individual pixels as single component types according to the highest relative component type probability for each individual pixel's color value;
compiling reference histograms of color values occurring within the identified portions of the reference video frame;
calculating color value density curves from the reference histograms;
compiling an overall histogram of color values within a sample video frame;
comparing the density curves to the overall histogram to obtain a scaling factor corresponding to each density curve;
and
scaling the density curves by scaling factors to obtain the relative component type probability curves.

7 more elements

Dependencies are inferred from the claim text.

Product inspection method and apparatus

Life of this patent

Product inspection method and apparatus

Life of this patent

Abstract

Claims60