AN FPGA-BASED ARCHITECTURE FOR REAL TIME IMAGE FEATURE EXTRACTION
Real-time image pattern recognition is a challenging task which involves image processing, feature extraction and pattern classification. It applies to a wide range of applications including multimedia , military and medical ones. Its high computational requirements force systems to use very expensive clusters, custom VLSI designs or even both. These approaches suffer from various disadvantages, such as high cost and long development times. Recent advances in fabri ....etc

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Definition
Real-time systems play a considerable role in our society, and they cover a spectrum from the very simple to the very complex. Examples of current real-time systems include the control of domestic appliances like washing machines and televisions, the control of automobile engines, telecommunication switching systems, military command and control systems, industrial process control, flight control systems, and space shuttle and aircraft avionics.

All of these involve gathering data from the environment, processing of gathered data ....etc

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Description
The m-files inside this zip file extracts features of single characters of english language based on their geometric properties from the input image. Two approaches are explained for extracting feature vectors. The final feature vector generated for my purpose had more 120 elements. The features are based on the basic geometric shapes that comprises a single character. It calculates how many basic line segments are there in the given character. Basic line segments like horizontal, vertical and diagonal are what looked for. Their len ....etc

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jane w s liu real time system exercise solution of real time system by jane liu

Written by a renowned expert, Real-Time System provides professionals and students with a comprehensive treatment of real-time computing and communication systems. The book covers the most recent advances in real-time operating systems and communications networks. Thus, this book serves as a vehicle for technology transition within the real-time system community of systems architects, designers chief scientists and technologists, and systems analysts. Jane Liu's su ....etc

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This article describes about modified band-pass filtered MFCC.Improved noise robustness is obtained by varying the time constants in each channel and adaptive gain compression of the envelope in each channel.This article also presents speech discrimination and
recognition results.
Mel-frequency cepstral coefficients (MFCCs),are not very robust for noise.Reasons include-the number of samples used to represent each frame is small compared to the original sampled waveform in most audio feature extraction processes.FFT followed by grouping into ....etc

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Abstract

Edge detection is an image processing technique for finding the boundaries of objects within images. It works by detecting discontinuities in brightness. Edge detection is used for image segmentation and data extraction in areas such as image processing, computer vision, and machine vision. ....etc

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matlab coding for wavelet based feature extraction for brain tumor MRI image ....etc

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Hey,
visit this thread for full report:
http://seminarsprojects.net/Thread-RTOS-Real-Time-Operating-Systems-full-report ....etc

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Abstract :
Watershed transformation is a powerful technique that can be efficiently used for image segmentation. Its use
for classifying and grading rice kernels has been discussed followed by its implementation on reconfigurable
devices. In this paper, we implement a watershed based segmentation algorithm on a Virtex-6 platform. The
main contribution of this work is the low execution time and minimal internal hardware resource occupation.
Watershed has been written in C-code and also in Verilog hardware descriptive language. The Ve ....etc

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Abstract
Edge detection is a basic and important subject in computer vision and image processing. In this paper we discuss several digital image processing techniques applied in edge feature extraction. Firstly, wavelet transform is used to remove noises from the image collected. Secondly, some edge detection operators such as Differential edge detection, Log edge detection, canny edge detection and Binary morphology are analyzed. And then according to the simulation results, the advantages and disadvantages of these edge detection ope ....etc

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