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Evaluation of the shape-varying structuring element in QRS detection for ECG compression

Tadejko P., Rakowski W.

Image Processing & Communications

2005

Vol. 10, no 2

27-38

Morphological operations are simple mathematical constructs, which have led to effective solution for many problems in signal and image processing. These solutions employ discrete operators (structuring element) and are applied to digitized signals. The paper presents the mathematical morphology approach to the recognition and classification of heart rhythms on the basis of electrocardiogram (EGG) waveforms. The main part in recognition is based on the morphological niters characterization of the QRS complexes. In this work, we present morphological filtering as a preliminary step for compression of ECG data using image compression algorithms. To corn-press the ECG data using for example JPEG2000, SPITH or other codec, the one-dimensional ECG sequence needs to be processed to produce a two-dimensional matrix. Detecting operator designed for creating sequence is controlled by the shape and size of the structuring element. We compare how shape and length of this element can affects sensitivity detection algorithm based on amplitude and slope. The performance of the algorithm is evaluated with standard MIT/BIll arrythmia database.

Automatic selection of structuring element for object classification through morphology

Chanda B., Bhattacharyya R.

Image Processing & Communications

1999

Vol. 5, no 1

67-79

How to select a structuring element for a given task is one of the most frequently asked questions in morphology. Present work tries to give a solution for a restricted class of problems, namely shape classification. In this work an algorithm that extracts distinctive structure of each of a given set of objects is proposed. The proposed algorithm is based on a new approach for computing distance transform.