Method of Oriented Contour Detection on Image Using Lorentz Function
| Autor: | Dmitry Kaplun, M. R. Kiladze, Pavel A. Lyakhov, Alexander Voznesensky, A.S. Abdulsalyamova |
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| Rok vydání: | 2020 |
| Předmět: |
Angle of rotation
business.industry Computer science Orientation (computer vision) ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition 02 engineering and technology Filter (signal processing) 010501 environmental sciences 01 natural sciences Convolutional neural network law.invention law Feature (computer vision) Digital image processing 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Cartesian coordinate system Artificial intelligence business Digital filter 0105 earth and related environmental sciences |
| Zdroj: | MECO |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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