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A Novel Steerable Filter in the Frequency Domain: The Rose Curve FilterMINTEMUR, O. , KAYA, H. , DEMIRCI, R.
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feature extraction, filtering, Fourier transforms, image processing, pattern recognition
image(10), recognition(8), processing(7), transform(6), contourlet(6), pattern(5), method(5), domain(5), design(5), yang(4)
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About this article
Date of Publication: 2021-05-31
Volume 21, Issue 2, Year 2021, On page(s): 49 - 58
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2021.02006
Web of Science Accession Number: 000657126200006
SCOPUS ID: 85107618537
Feature extraction in image processing is a difficult task. To do this, a filter bank is one of the most used techniques. To extract a feature, the image is masked with filters in prepared filter banks, one by one. If a greater number of features can be extracted from an image, the task is easier. Thus, identifying more features is desirable in many image processing applications. However, filter preparation can be troublesome because of the difficulties in determining a filters parameters such as direction. Limitations of the selected filter are another issue. Thus, an easy-to-use filter with few parameters and directional flexibility is a desirable choice. For these reasons, a novel steerable type of filter is proposed in this study. The proposed rose curve filter uses Lemniscate shapes derived from the rose curves to extract image features in the frequency domain. It has three parameters, fewer than other filters, and has directional flexibility. It can also extract images in more than one direction. Experimental results show that it is effective in feature extraction during image processing.
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