Source code level software defect detection has gone from state of the art to a software engineering best practice. Automated code analysis tools streamline many of the aspects of formal code inspections but have the drawback of being difficult to construct and either prone to false positives or severely limited in the set of defects that can be detected. Machine learning technology provides th...

Fabric defect detection and classification plays an important role in inspection of fabric products. Many fabric defects are very small and undistinguishable, which can be detected only by monitoring the variation in the intensity. Currently, in almost all the fabric industries the process of defect detection is done manually using skilled labor. An automated defect detection and identification...

An algorithm with linear filters and morphological operations has been proposed for automatic fabric defect detection. The algorithm is applied off-line and real-time to denim fabric samples for five types of defects. All defect types have been detected successfully and the defective regions are labeled. The defective fabric samples are then classified by using feed forward neural network metho...

This paper investigates various approaches for automated inspection of textured materials using Gabor filters. A new supervised defect detection approach is used to detect defect in textile web. Unsupervised web inspection is used with multichannel filtering scheme. This scheme establishes high computational savings and results in high quality of defect detection. The experimental results condu...

Acoustic micro imaging has been proven to be sufficiently sensitive for micro defect detection. In this study, we propose a sparse reconstruction method for acoustic micro imaging. A finite element model with a micro defect is developed to emulate the physical scanning. Then we obtain the point spread function, a blur kernel for sparse reconstruction. We reconstruct deblurred images from the ov...

A model is presented for defect insertion and detection in software development. The model, which is based on a high-level, generic concept of the software life cycle, allows for the estimation of final defect content based on estimates of several process factors: defect insertion rate, defect detection ratio, spreading ratio and traceability factor. It is suggested that the model has potential...

A model is presented for defect insertion and detection in software development. The model, which is based on a high-level, generic concept of the software life cycle, allows for the estimation of final defect content based on estimates of several process factors: defect insertion rate, defect detection ratio, spreading ratio and traceability factor. It is suggested that the model has potential...

Conventional VLSI testing methods are challenged by changing circuit sensitivities and emerging defect mechanisms resulting from the use of new fabrication materials in very deep submicron processes. For example, the change from a subtractive aluminum process to damascene Cu may lead to more particlerelated blocked-etch resistive opens. Technology scaling also increases the probability of resis...