We use Abstract 3D models for sketch recognition. The models should be abstract because sketches do not contain texture information which is present in the usual 3D models. Zernike moment descriptors are used for recognition. These descriptors do rotation invariant recognition and also provide the angle of rotation. Also the same concept can be extended to 3D viewpoint detection of the sketch.

Handwriting recognition is a rich and complex issue. Some of its problems include the large shape variations in human handwriting. Classifier combination contributes in increasing the classification accuracy compared to the performance of individual classifier. In this paper, we present an online handwriting recognizer based on classifier combination according to holistic approach. We propose t...

In this paper, an algorithm is proposed for the classification of malignancy in mammogram. The types of malignancy can be classified as circumscribed, speculated, architectural distortion, miscellaneous, asymmetry and calcification. Chebyshev moments (CM), being discrete, are capable to combat the discritisation errors as compared to Zernike Moments (ZM), which are continuous moments. It is als...

Identification of visual words and writings has long been one of the most essential and the most attractive operations in the field of image processing which has been studied since the last few decades and includes security, traffic control, fields of psychology, medicine, and engineering, etc. Previous techniques in the field of identification of visual writings are very similar to each other ...

Zernike polynomials are a well known set of functions that find many applications in image or pattern characterization because they allow to construct shape descriptors that are invariant against translations, rotations or scale changes. The concepts behind them can be extended to higher dimension spaces, making them also fit to describe volumetric data. They have been less used than their prop...

Vibration mode-shape comparison between numerical models and experimental data is an essential step in the study of structural finite element model (FEM) updating. The Modal Assurance Criterion (MAC) is the most popular method for such comparison at the moment, which works perfectly well for small and medium sized structures. MAC provides a measure of closeness between the predicted and measure...