CFlowchartEditor is an extension of CDiagramEditor. CDiagramEditor is a vector editor, with a CWnd-derived window (CDiagramEditor), a data container (CDiagramEntityContainer) holding the draw-objects, undo stack and managing copy and paste, and objects derived from CDiagramEntity representing objects drawn on screen. CDiagramEditor lacks one feature (that is difficult to implement in both simple and general fashion) - links. Manually maintaining links in a - for example - flowchart or network topography map is unwieldy. Therefore, I ve created a reference implementation for one way of adding this functionality.
AdaBoost is an efficient tool in machine learning. It can combine a series of weak learners into a strong learner. Besides pattern classification, it also can be applied into feature selection. This document explains the use of AdaBoost.
This document is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will gives an overview of three fundamental tasks in signal and image processing : signal, denoising and compression. These scripts are selfs contents (needed additional Matlab functions can be downloaded while reading the lectures).
Each one of these five lectures should take between 1h and 2h in order to tests the various features of the scripts. One should copy/paste the provided code into a file names e.g. tp1.m, and launch the script directly from Matlab comand line > tp1 . Some of the scripts contains "holes" that you should try to fill on your own.
I also provide the complete correction of these lectures as a set of Matlab scripts, but you should try as much as possible to avoid using them.
//
// Histogram Sample
// This sample shows how to use the Sample Grabber filter for video image processing.
// Conceptual background:
// A histogram is just a frequency count of every pixel value in the image.
// There are various well-known mathematical operations that you can perform on an image
// using histograms, to enhance the image, etc.
// Histogram stretch (aka automatic gain control):
// Stretches the image histogram to fill the entire range of values. This is a "point operation,"
// meaning each pixel is scaled to a new value, without examining the neighboring pixels. The
// histogram stretch does not actually require you to calculate the full histogram. The scaling factor
// is calculated from the minimum and maximum values in the image.
sfrmat is a Matlab function that provides a spatial frequency response* (SFR) from a digital image file containing a slanted-edge feature. The specific edge-gradient algorithm follows the intent of the standard ISO 12233, developed by Technical Committee ISI/TC 42, for resolution measurements for electronic still pictorial cameras.
An optimal neuron evolution algorithm for the restoration
of linearly distorted images is presented in this paper. The proposed
algorithm is motivated by the symmetric positive-definite quadratic programming
structure inherent in restoration. Theoretical analysis and experimental
results show that the algorithm not only significantly increases
the convergence rate of processing, hut also produces good restoration
results. In addition, the algorithm provides a genuine parallel processing
structure which ensures computationally feasible spatial domain image
restoration
Digital Signal and Image Processing Using MATLAB
The most important theoretical aspects of image and signal processing (ISP) for both deterministic and random signals are covered in this guide to using MATLAB® . The discussion is also supported by exercises and computer simulations relating to real applications such as speech processing and fetal-heart–rhythm tracking, and more than 200 programs and functions for numerical experiments are provided with commentary.
Semantic analysis of multimedia content is an on going research
area that has gained a lot of attention over the last few years.
Additionally, machine learning techniques are widely used for multimedia
analysis with great success. This work presents a combined approach
to semantic adaptation of neural network classifiers in multimedia framework.
It is based on a fuzzy reasoning engine which is able to evaluate
the outputs and the confidence levels of the neural network classifier, using
a knowledge base. Improved image segmentation results are obtained,
which are used for adaptation of the network classifier, further increasing
its ability to provide accurate classification of the specific content.
Range imaging offers an inexpensive and accurate means for
digitizing the shape of three-dimensional objects. Because most
objects self occlude, no single range image suffices to describe the
entire object. We present a method for combining a collection of
range images into a single polygonal mesh that completely describes
an object to the extent that it is visible from the outside.
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