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Code Listing by Theodoros Giannakopoulos

Code 1-9 of 9   

Theodoros Giannakopoulos

Feature extraction (as in most pattern recognition problems) is maybe the most important step in audio classification tasks. The provided Matlab code computes some of the basic audio features for groups of sounds stored in WAV files. Furthermore, a simple class separability measure, based on feature histograms is used for...

Content-based image retrieval is the task of searching images in databases by analyzing the image contents. In this demo, a simple image retrieval method is presented, based on the color distribution of the images. The user simply provides an...

The current Matlab-code can be used for real-time audio and image processing. Fixed-length segments of audio data are recorded from soundcard's input and an image is also captured in each block. In particular, the provided code does the...

This is a GUI that demonstrates some basic image processing functionalities, e.g., color filtering, motion filtering, etc. The user can load any of the basic image file types and then generate a secondary image based on the provided...

The provided functions demonstrate a histogram-based measure for class separability, given the samples from two classes (binary classification problem). The proposed error classification estimation method is described in (B) and it is based on...

This demo provides a simple GUI for basic filtering of audio data. Using the GUI you can:

* Load audio data stored in a .wav file.
* Generate uniform noise in specific audio frequencies, using lowpass, highpass or bandpass...

AudioAnnotation Demo v.1.0 is an open source demo implemented in Matlab(R) for manual segmentation and annotation of audio files. You can use it for defining the ground truth, in order to check your segmentation-classification algorithm's...

function createAnimatedGifFromWav(wavFileName, windowLength, Width, framesPerSec)

- wavFileName: the name of the .wav file to read
- windowLength: the length (in seconds) of each window to be plotted in...

This is a simple method for silence removal and segmentation of audio streams that contain speech. The method is based in two simple audio features (signal energy and spectral centroid). As long as the feature sequences are extracted, as...