Abstract: A computerized inspection system is described for detecting the presence of non-uniformity defects and providing output indicative of a severity of each type of non-uniformity defect. Techniques are described that increase the throughput of the inspection system. Algorithmic and hardware approaches are described to significantly decrease the average amount of time required to inspect a given quantity of material that is expected to be mostly uniform. The techniques described herein involve dynamic selection of which image features to compute by starting with a base feature set and only triggering additional feature computations as needed until the features are sufficient to compute a severity for each type of non-uniformity defect. The number of features extracted and the order in which the features are extracted is dynamically determined in real-time to reduce a cost associated with the feature extraction.

Abstract: A system is described for detecting the presence of non-uniformity patterns and providing output indicative of a severity of each type of non-uniformity pattern. The system includes a computerized rating tool that assists a user in efficiently and consistently assigning expert ratings (i.e., labels) to a large collection of training images representing samples of a given product. In addition, the rating software develops a model that allows a computerized inspection system to detect the presence of non-uniformity patterns in a manufactured web material in real time and provide output indicative of a severity level of each pattern on a continuous scale. The system also includes algorithmic and hardware approaches to significantly that increase the throughput of the inspection system.

Abstract: A computerized rating tool is described that assists a user in efficiently and consistently assigning expert ratings (i.e., labels) to a large collection of training images representing samples of a given product. The rating tool provides mechanisms for visualizing the training images in an intuitive and configurable fashion, including clustering and ordering the training images. In some embodiments, the rating tool provides an easy-to-use interface for exploring multiple types of defects represented in the data and efficiently assigning expert ratings. In other embodiments, the computer automatically assigns ratings (i.e., labels) to the individual clusters containing the large collection of digital images representing the samples.

Abstract: A system is described for detecting the presence of non-uniformity patterns and providing output indicative of a severity of each type of non-uniformity pattern. The system includes a computerized rating tool that assists a user in efficiently and consistently assigning expert ratings (i.e., labels) to a large collection of training images representing samples of a given product. In addition, the rating software develops a model that allows a computerized inspection system to detect the presence of non-uniformity patterns in a manufactured web material in real time and provide output indicative of a severity level of each pattern on a continuous scale. The system also includes algorithmic and hardware approaches to significantly that increase the throughput of the inspection system.

Abstract: A computerized inspection system is described for detecting the presence of non-uniformity defects and providing output indicative of a severity of each type of non-uniformity defect. Techniques are described that increase the throughput of the inspection system. Algorithmic and hardware approaches are described to significantly decrease the average amount of time required to inspect a given quantity of material that is expected to be mostly uniform. The techniques described herein involve dynamic selection of which image features to compute by starting with a base feature set and only triggering additional feature computations as needed until the features are sufficient to compute a severity for each type of non-uniformity defect. The number of features extracted and the order in which the features are extracted is dynamically determined in real-time to reduce a cost associated with the feature extraction.

Abstract: A computerized inspection system is described for detecting the presence of non-uniformity defects in a manufactured web material and for providing output indicative of a severity level of each defect. The system provides output that provides the severity levels of the non-uniformity defects in real-time on a continuous scale. Training software processes a plurality of training samples to generate a model, where each of the training samples need only be assigned one of a set of discrete rating labels for the non-uniformity defects. The training software generates the model to represent a continuous ranking of the training images, and the inspection system utilizes the model to compute the severity levels of the web material on a continuous scale in real-time without limiting the output to the discrete rating labels assigned to the training samples.

Abstract: A computerized rating tool is described that assists a user in efficiently and consistently assigning expert ratings (i.e., labels) to a large collection of training images representing samples of a given product. The rating tool provides mechanisms for visualizing the training images in an intuitive and configurable fashion, including clustering and ordering the training images. In some embodiments, the rating tool provides an easy-to-use interface for exploring multiple types of defects represented in the data and efficiently assigning expert ratings. In other embodiments, the computer automatically assigns ratings (i.e., labels) to the individual clusters containing the large collection of digital images representing the samples.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Systems and methods for calibrating a web inspection system.

Abstract: Systems and methods for calibrating a web inspection system.