This book presents an overview of the guidelines and strategies for transitioning an image or video processing algorithm from a research environment into a real-time constrained environment. Such guidelines and strategies are scattered in the literature of various disciplines including image processing, computer engineering, and software engineering, and thus have not previously appeared in one place. By bringing these strategies into one place, the book is intended to serve the greater community of researchers, practicing engineers, industrial professionals, who are interested in taking an image or video processing algorithm from a research environment to an actual real-time implementation on a resource constrained hardware platform. These strategies consist of algorithm simplifications, hardware architectures, and software methods. Throughout the book, carefully selected representative examples from the literature are presented to illustrate the discussed concepts. After reading the book, the readers are exposed to a wide variety of techniques and tools, which they can then employ for designing a real-time image or video processing system of interest. KEYWORDSReal-time image and video processing, Real-time implementation strategies, Algorithmic simplifications for real-time image and video processing, Hardware platforms for real-time image and video processing, Software methods for real-time image and video processing v

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Auto-focus (AF) is a common feature in consumer level digital and cell-phone cameras. Face-based AF, or AF based on face detection, has become of interest due to the fact that the majority of pictures captured by consumers are of human faces. While many face detection algorithms exist in the literature, very few of them are actually suitable for real-time deployment on resource limited digital or cell-phone camera processors. In this paper, a face-detection algorithm combining a Gaussian skin color model with a computationally efficient sub-block postprocessing scheme is introduced to address the realtime constraints encountered in digital and cellphone cameras. This approach has been implemented in conjunction with our previously developed rulebased AF method in order to achieve real-time facedbased AF on the Texas Instruments programmable TMS320DM350 digital camera processor.

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