Patent ID: 6650779
Filing Date: 2003-11-18
Classification: G01N,G06K,G06T

Abstract:
An apparatus for analyzing a 2-D representation of an object, said apparatus comprising:at least one sensor disposed to capture a 2-D representation of at least a portion of an object; a memory that stores at least a portion of said 2-D representation received from said sensor; a processor containing a program module operative to: receive said stored portion of said 2-D representation; derive a plurality of features from said stored portion of said representation; provide said features to a multi-dimensional wavelet neural network, said multi-dimensional wavelet neural network incorporating a learning technique from the following group consisting of structure learning, parameter learning, or combined parameter and structure learning for classification performance, wherein said features are compared to a predetermined fault pattern to determine if the features represent a defect; and produce a classification output indicative of whether said stored portion of said representation comprises a defect; and a decision logic unit which receives said features and said classification output and determines if comparing said features to said predetermined fault patterns results in a classification output which is potentially indicative of a predetermined fault pattern, wherein said decision logic unit resolves said classification output by referencing said multi-dimensional wavelet neural network to provide a final declaration as to whether the classification output should be classified as a defect.