Sketch recognition

About: Sketch recognition is a research topic. Over the lifetime, 1611 publications have been published within this topic receiving 40284 citations.

Pattern Recognition and Image Processing

Abstract: Extensive research and development has taken place over the last 20 years in the areas of pattern recognition and image processing. Areas to which these disciplines have been applied include business (e. g., character recognition), medicine (diagnosis, abnormality detection), automation (robot vision), military intelligence, communications (data compression, speech recognition), and many others. This paper presents a very brief survey of recent developments in basic pattern recognition and image processing techniques.

Computer Recognition Systems 3

Abstract: The computer recognition systems are nowadays one of the most promising directions in artificial intelligence. This book is the most comprehensive study of this field. It contains a collection of 69 carefully selected articles contributed by experts of pattern recognition. It reports on current research with respect to both methodology and applications. In particular, it includes the following sections: Features, learning and classifiers, Image processing and computer vision, Speech and word recognition, Medical applications, Miscellaneous applications. This book is a great reference tool for scientists who deal with the problems of designing computer pattern recognition systems. Its target readers can be the as well researchers as students of computer science, artificial intelligence or robotics.

Symbol Recognition: Current Advances and Perspectives

Abstract: The recognition of symbols in graphic documents is an intensive research activity in the community of pattern recognition and document analysis. A key issue in the interpretation of maps, engineering drawings, diagrams, etc. is the recognition of domain dependent symbols according to a symbol database. In this work we first review the most outstanding symbol recognition methods from two different points of view: application domains and pattern recognition methods. In the second part of the paper, open and unaddressed problems involved in symbol recognition are described, analyzing their current state of art and discussing future research challenges. Thus, issues such as symbol representation, matching, segmentation, learning, scalability of recognition methods and performance evaluation are addressed in this work. Finally, we discuss the perspectives of symbol recognition concerning to new paradigms such as user interfaces in handheld computers or document database and WWW indexing by graphical content.

Fast recognition algorithm processing, systems and methods

Abstract: Systems and methods of quickly recognizing or differentiating many objects are presented. Contemplated systems include an object model database storing recognition models associated with known modeled objects. The object identifiers can be indexed in the object model database based on recognition features derived from key frames of the modeled object. Such objects are recognized by a recognition engine at a later time. The recognition engine can construct a recognition strategy based on a current context where the recognition strategy includes rules for executing one or more recognition algorithms on a digital representation of a scene. The recognition engine can recognize an object from the object model database, and then attempt to identify key frame bundles that are contextually relevant, which can then be used to track the object or to query a content database for content information.