US 2019/0318469 A1 · DEFECT DETECTION USING COHERENT LIGHT ILLUMINATION AND ARTIFICIAL NEURAL NETWORK ANALYSIS OF SPECKLE PATTERNS

Abstract

A system and method for detecting defects in an object includes illuminating the object with a coherent light, recording the a speckle pattern of the coherent light reflected and/or scattered and/or transmitted from the object, and analyzing the speckle pattern using a trained artificial neural network to determine whether defects are present in the object and the types of defects. To train the neural network, sample objects having known types of defects or no defects are illuminated with a coherent light and the speckle patterns are recorded. The speckle patterns are labeled with the type of defects in the corresponding sample objects, and used as training data to train the network. The technique analyzes the speckle patterns directly, and does not require phase recovery and object shape reconstruction. The technique is useful for defect inspection in industrial production to detect defects such as scratches, air bubbles, deformation, stains, etc.

Claims18

Dependent claims

A system for detecting defects in a test object, comprising:

a coherent light source generating a coherent illumination light, the coherent light source being positioned to illuminate the test object with the coherent illumination light;
a two-dimensional image sensor, positioned to record a light pattern of the coherent illumination light after the coherent illumination light has interacted with the test object, the light pattern containing a speckle pattern;
and
a data processing apparatus coupled to the image sensor, the data processing apparatus implementing a trained artificial neural network configured to analyze the light pattern to determine whether any defect is present in the test object and at least one type of the defect that is present.

1 more element

A method for detecting defects in a test object, comprising:

obtaining a plurality of sample objects, each sample object either having no defects or having known types of defects;
illuminating each sample object with a coherent illumination light;
for each sample object being illuminated, using a two-dimensional image sensor, recording a light pattern of the coherent illumination light after the coherent illumination light has interacted with the sample object, the light pattern containing a speckle pattern, to obtain a plurality of light patterns corresponding to the plurality of sample objects;
labeling each light pattern with at least one label indicating the type of types of defects or an absence of defects in the corresponding sample object, to generate a plurality of labeled light patterns;
obtaining an untrained artificial neural network implemented in a data processing apparatus;
training the untrained artificial neural network using the plurality of labeled light patterns as training data, to produce a trained artificial neural network;
illuminating the test object with a coherent illumination light;
using a two-dimensional image sensor, recording a light pattern of the coherent illumination light after the coherent illumination light has interacted with the test object, the light pattern containing a speckle pattern;
and
using a data processing apparatus which implements the trained artificial neural network, analyzing the light pattern to determine whether any defect is present in the test object and at least one type of the defect that is present.

7 more elements

Dependencies are inferred from the claim text.

Defect detection using coherent light illumination and artificial neural network analysis of speckle patterns

Life of this patent

Defect detection using coherent light illumination and artificial neural network analysis of speckle patterns

Life of this patent

Abstract

Claims18