Download PDF by Dr. Muhammad Sarfraz: Computer-aided intelligent recognition techniques and

By Dr. Muhammad Sarfraz

ISBN-10: 0470094141

ISBN-13: 9780470094143

Clever reputation tools have lately confirmed to be integral in numerous smooth industries, together with desktop imaginative and prescient, robotics, scientific imaging, visualization and the media. additionally, they play a severe function within the conventional fields comparable to personality reputation, average language processing and private identity.

This state of the art ebook attracts jointly the newest findings of specialists and researchers from around the world. it's a well timed advisor for all these require accomplished, state of the art suggestion at the current prestige and destiny capability of clever attractiveness technology.

Computer-Aided clever acceptance concepts and Applications:

  • Provides the person neighborhood with platforms and instruments for software in a really wide variety of components, together with: IT, schooling, safeguard, banking, police, postal companies, production, mining, medication, multimedia, leisure, communications, info visualization, wisdom extraction, trend category and digital reality.
  • Disseminates info in a plethora of disciplines, for instance trend acceptance, AI, picture processing, laptop imaginative and prescient and pix, neural networks, cryptography, fuzzy common sense, databases, evolutionary algorithms, form and numerical analysis.
  • Illustrates all concept with real-world examples and case studies.

This priceless source is vital examining for desktop scientists, engineers, and specialists requiring up to date complete information at the most recent advancements in computer-aided clever attractiveness options and purposes. Its specific, useful technique could be of curiosity to senior undergraduate and graduate scholars in addition to researchers and specialists within the box of clever recognition.

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This neuron contains an extra parameter, the standard deviation value, for use in the transfer function. The RBF network consists of three layers, an input layer of dummy neurons, a hidden layer of radial neurons and an output layer of linear neurons. Unlike the other architectures, which contain a fixed number of nodes, the RBF architecture is dynamic, in that it adds neurons to its hidden layer as it is trained. There are a total of 20 nodes in the hidden layer in the implemented systems, determined heuristically.

4 is discarded on the basis of the slope of the line P0 Pend . 3 Vertical Edge Matching In this phase, the width to height ratio of the license plate is used to match the vertical edges for finding the region of where there is a probability of a license plate. The ratio of width to height of Saudi Arabian license plates is about 2:1. 2(d) is extracted, having several vertical regions. Only two of the regions could be the possible boundary of the license plate. The task of vertical edge matching is to find out the correct pair of regions that include the license plate.

Conversion to a grayscale facilitates the extraction of the license plate. 2(b). 4. License Plate Extraction License plate extraction is the key step in an LPR system, it influences the accuracy of the system significantly. The goal of this phase is, given an input image, to produce a number of candidate regions with high probability of containing a license plate. In the adopted approach, extraction of the license plate is divided into three steps which are explained in the following subsections.

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Computer-aided intelligent recognition techniques and applications by Dr. Muhammad Sarfraz


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