Abstract. Object extraction from gray-tone images involve handling of inherent uncertainties in an image. Traditionally fuzzy set theoretic techniques are used for this purpose. However, roughness and limited discernibility of objects is another important aspect of image uncertainty. In this article we propose an algorithm for selection of intensity threshold for object extraction by optimizing a roughness measure of the fuzzy set corresponding to the image object. The rough-fuzzy algorithm is tested on some benchmark images.

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In today's competitive environment for software products, quality is an important characteristic. The development of large-scale software products is a complex and expensive process. Testing plays a very important role in ensuring product quality. Improving the software development process leads to improved product quality. We propose a queueing model based on re-entrant lines to depict the process of software modules undergoing testing/debugging, inspections and code reviews, verification and validation, and quality assurance tests before being accepted for use. Using the re-entrant line model for software testing, bounds on test times are obtained by considering the state transitions for a general class of modules and solving a linear programming model. Scheduling of software modules for tests at each process step yields the constraints for the linear program. The methodology presented is applied to the development of a software system and bounds on test times are obtained. These bounds are used to allocate time for the testing phase of the project and to estimate the release times of software.

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