An Edge Detection Algorithm of Anti-harmonic Image Based on Tensor Form Article Swipe
Edge detection of image is used to improve the visual recognition ability of the pattern by identifying points with obvious variation of brightness in a digital image.In the case of uneven conversion of color information of antiharmonic image pixel, edge detection becomes difficult.Traditional edge detection algorithm of anti-harmonic image adopts tensor model, as due to relatively simple structure of the tensor vector and operation, the performance of edge detection is poor.Therefore, An edge detection algorithm of anti-harmonic image based on colored tensor form is proposed.It starts from building the tensor model of colored and anti-harmonic image, accurately measuring the relationship between pixels by means of rich computing of tensor, finding the maximum and minimum values of the first derivative of the image to detect the boundary in the space of tensor form, and finally improve the algorithm based on the color tensor morphological operators of referenced total order.Simulation results show that the anti-harmonic mean of the proposed algorithm is higher than the conventional algorithms because it not only takes into account the correlation between the color components, but also considers the conversion feature of color information, which has superior performance of detection.
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- Type
- article
- Language
- en
- Landing Page
- http://doi.org/10.2174/1874444301507011705
- http://benthamopen.com/contents/pdf/TOAUTOCJ/TOAUTOCJ-7-1705.pdf
- OA Status
- bronze
- References
- 8
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2214609536
All OpenAlex metadata
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- OpenAlex ID
-
https://openalex.org/W2214609536Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.2174/1874444301507011705Digital Object Identifier
- Title
-
An Edge Detection Algorithm of Anti-harmonic Image Based on Tensor FormWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-10-09Full publication date if available
- Authors
-
Li XiangList of authors in order
- Landing page
-
https://doi.org/10.2174/1874444301507011705Publisher landing page
- PDF URL
-
https://benthamopen.com/contents/pdf/TOAUTOCJ/TOAUTOCJ-7-1705.pdfDirect link to full text PDF
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
- OA URL
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https://benthamopen.com/contents/pdf/TOAUTOCJ/TOAUTOCJ-7-1705.pdfDirect OA link when available
- Concepts
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Enhanced Data Rates for GSM Evolution, Tensor (intrinsic definition), Edge detection, Computer science, Image (mathematics), Harmonic, Algorithm, Artificial intelligence, Pattern recognition (psychology), Computer vision, Mathematics, Image processing, Physics, Pure mathematics, AcousticsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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8Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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