Real-time feature extraction from video stream data for stream ...

ai.cs.uni.dortmund.de

Real-time feature extraction from video stream data for stream ...

6.2. Image Feature Extraction with RapidMiner

By using the Multiple Color Image Opener, I loop over all images

in the folder created by xuggler. The process shown in figure 6.9

is the inner process of the MCIO-operator and is hence executed

for every image. First the image gets multiplied seven times. One

of the seven images is kept as it is, the others are transformed by

selecting a single color channel only, calculating the difference

image, converting the image to grayscale, or applying border

detection. Afterwards the Global Feature Extractor from a Single

Image-operator is applied to each of the resulting images

in order to extract features from the images. In order to save

computational time, the operator is not always used to its’ full

extent. For example color histograms are only extracted of the

Figure 6.8.: Multiple

Color Image

Opener

original image. After renaming the extracted features and adding an id in order to be

able to join the resulting example sets, the extracted features are written into a .csv-file.

As the result of the whole process, I gained a set of 80 features per frame. A complete

list of the features extracted with the RapidMiner IMMI is included in the appendix.

Figure 6.9.: The overall feature extraction process in RapidMiner

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