Fuzzy logic-based embedded system for video de-interlacing

Video de-interlacing algorithms perform a crucial task in video processing. Despite these algorithms are developed using software implementations, their implementations in hardware are required to achieve real-time operation. This paper describes the development of an embedded system for video de-interlacing. The algorithm for video de-interlacing uses three fuzzy logic-based systems to tackle three relevant features in video sequences: motion, edges, and picture repetition. The proposed strategy implements the algorithm as a hardware IP core on a FPGA-based embedded system. The paper details the proposed architecture and the design methodology to develop it. The resulting embedded system is verified on a FPGA development board and it is able to de-interlace in real-tim

A General Hardware/Software Co-design Methodology for Embedded Signal Processing and Multimedia Workloads

This paper presents a hardware/software co-design methodology for partitioning real-time embedded multimedia applications between software programmable DSPs and hardware based FPGA coprocessors. By following a strict set of guidelines, the input application is partitioned between software executing on a programmable DSP and hardware based FPGA implementation to alleviate computational bottlenecks in modern VLIW style DSP architectures used in embedded systems. This methodology is applied to channel estimation firmware in 3.5G wireless receivers, as well as software based H.263 video decoders. As much as an 11x improvement in runtime performance can be achieved by partitioning performance critical software kernels in these workloads into a hardware based FPGA implementation executing in tandem with the existing host DSP.Nokia Inc.Texas InstrumentsNational Science Foundatio

Narrative Generation in Entertainment: Using Artificial Intelligence Planning

From the field of artificial intelligence (AI) there is a growing stream of technology capable of being embedded in software that will reshape the way we interact with our environment in our everyday lives. This ‘AI software’ is often used to tackle more mundane tasks that are otherwise dangerous or meticulous for a human to accomplish. One particular area, explored in this paper, is for AI software to assist in supporting the enjoyable aspects of the lives of humans. Entertainment is one of these aspects, and often includes storytelling in some form no matter what the type of media, including television, films, video games, etc. This paper aims to explore the ability of AI software to automate the story-creation and story-telling process. This is part of the field of Automatic Narrative Generator (ANG), which aims to produce intuitive interfaces to support people (without any previous programming experience) to use tools to generate stories, based on their ideas of the kind of characters, intentions, events and spaces they want to be in the story. The paper includes details of such AI software created by the author that can be downloaded and used by the reader for this purpose. Applications of this kind of technology include the automatic generation of story lines for ‘soap operas’

A MPEG Decoder in SHIM

The emergence of world-wide standards for video compression has created a demand for design tools and simulation resources to support algorithm research and new product development. Because of the need for subjective study in the design of video compression algorithms it is essential that flexible yet computationally efficient tools be developed. For this project, we plan to implement a MPEG standard using the SHIM programming language. The SHIM is a software/hardware integration language whose aim is to provide communication between hardware and software while providing deterministic concurrency. The focus of this project will be to emphasize the efficiency of the SHIM language in embedded applications as compared to other existing implementations

A Novel Video/Photo Recorder Using an Online Motion Sensor-Triggered Embedded System

In recent years embedded systems have gained more importance. These systems are especially dedicated to specific tasks which are handled by highly optimized solutions. One of the interesting areas of embedded systems use is multi-media. Producing, processing, streaming various multimedia types and interacting with the physical environment is very common today. Similar to these studies, controlling and observing the specified area by multi-media tools are the necessities for many reasons such as security. This paper presents a method of video and photo recording of any moving object by using open source operation system (Raspbian- a distribution of Linux) and software (Python – a high-level programming language). The system is triggered by a motion sensor and it collects visual data from a specified area for limited duration. The collected data is published on internet via dedicated web site. Keywords: Photo and Video Recorder, Open Source Platforms, Embedded System

Control Software for Advanced Video Guidance Sensor

Embedded software has been developed specifically for controlling an Advanced Video Guidance Sensor (AVGS). A Video Guidance Sensor is an optoelectronic system that provides guidance for automated docking of two vehicles. Such a system includes pulsed laser diodes and a video camera, the output of which is digitized. From the positions of digitized target images and known geometric relationships, the relative position and orientation of the vehicles are computed. The present software consists of two subprograms running in two processors that are parts of the AVGS. The subprogram in the first processor receives commands from an external source, checks the commands for correctness, performs commanded non-image-data-processing control functions, and sends image data processing parts of commands to the second processor. The subprogram in the second processor processes image data as commanded. Upon power-up, the software performs basic tests of functionality, then effects a transition to a standby mode. When a command is received, the software goes into one of several operational modes (e.g. acquisition or tracking). The software then returns, to the external source, the data appropriate to the command