Talk · Mediterranean Conference on Embedded Computing · June 1, 2020

Method of Oriented Contour Detection on Image Using Lorentz Function

Pavel Alekseyevich Lyakhov, Albina S. Abdulsalyamova, Mariya R. Kiladze, Dmitrii Kaplun, Alexander S. Voznesensky

Abstract

The paper proposes a new method of oriented contour detection on images using the Lorentz function. The first distinguishing feature of the development is the ability to adjust the size of the filter mask to be able to vary the distance between the analyzed differences at the boundaries of the analyzed image areas. The second feature is the ability to pre-set the angle of rotation of the coordinate plane, which determines the orientation of the filter. In addition, the proposed filter has a minimum number of zones with different signs, which distinguishes it from the known Gabor filters. The proposed method can be used in various fields of digital image processing, but the most promising, in our opinion, is the use of the proposed filters in convolutional neural networks instead of convolutional layer neurons that are responsible for distinguishing features.

Image and Object Detection TechniquesAdvanced Neural Network ApplicationsImage Retrieval and Classification TechniquesLorentz functionedge detectionconvolutional neural networks

Method of Oriented Contour Detection on Image Using Lorentz Function

Abstract

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