About: Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation

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An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
Creator	Qingge, Letu Yang, Pei Xing, Jiangwa
Source	Medline; PMC
abstract	Otsu's algorithm is one of the most well-known methods for automatic image thresholding. 2D Otsu's method is more robust compared to 1D Otsu's method. However, it still has limitations on salt-and-pepper noise corrupted images and uneven illumination images. To alleviate these limitations and improve the overall performance, here we propose an improved 2D Otsu's algorithm to increase the robustness to salt-and-pepper noise together with an adaptive energy based image partition technology for uneven illumination image segmentation. Based on the partition method, two schemes for automatic thresholding are adopted to find the best segmentation result. Experiments are conducted on both synthetic and real world uneven illumination images as well as real world regular illumination cell images. Original 2D Otsu's method, MAOTSU_2D, and two latest 1D Otsu's methods (Cao's method and DVE) are included for comparisons. Both qualitative and quantitative evaluations are introduced to verify the effectiveness of the proposed method. Results show that the proposed method is more robust to salt-and-pepper noise and acquires better segmentation results on uneven illumination images in general without compromising its performance on regular illumination images. For a test group of seven real world uneven illumination images, the proposed method could lower the ME value by 15% and increase the DSC value by 10%.
has issue date	2020-08-11(xsd:dateTime)
bibo:doi	10.1155/2020/5047976
bibo:pmid	32849864
has license	cc-by
sha1sum (hex)	4eafc3af38267cbb54cb4d7ca5f1fc5edd9cb195
schema:url	https://doi.org/10.1155/2020/5047976
resource representing a document's title	Robust 2D Otsu's Algorithm for Uneven Illumination Image Segmentation
has PubMed Central identifier	PMC7439172
has PubMed identifier	32849864
schema:publication	Comput Intell Neurosci
resource representing a document's body	covid:4eafc3af38267cbb54cb4d7ca5f1fc5edd9cb195#body_text
is schema:about of	named entity 'robustness' named entity 'acquires' named entity 'schemes' named entity 'quantitative' named entity 'images' named entity 'evaluations' named entity 'group' named entity 'illumination' named entity 'test' named entity 'illumination' named entity 'VALUE' named entity 'IMAGE SEGMENTATION' named entity 'BEST' named entity 'REGULAR' named entity 'NOISE' named entity 'LOWER' named entity 'ENERGY' named entity 'ILLUMINATION' covid:arg/4eafc3af38267cbb54cb4d7ca5f1fc5edd9cb195 named entity 'DSC' named entity 'salt-and-pepper noise' named entity 'verify' named entity 'result' named entity 'images' named entity 'corrupted' named entity 'qualitative' named entity 'cell' named entity 'real' named entity 'Otsu' named entity 'Robust' named entity 'image segmentation' named entity 'salt-and-pepper noise' named entity 'Otsu's method' named entity 'Otsu's method' named entity 'algorithm' named entity 'DSC' named entity 'pixel' named entity 'Otsu's method' named entity 'Otsu's method' named entity 'energy function' named entity 'salt-and-pepper noise' named entity 'Otsu's method' named entity 'Otsu's method' named entity 'pixels' named entity 'pixels' named entity 'Otsu's method' named entity 'Otsu's method' named entity 'index number' named entity 'Otsu's method' named entity 'metaheuristic' named entity 'infectious diseases' named entity 'Neuroscience' named entity 'one-dimensional' named entity 'histogram' named entity 'gray level' named entity 'Otsu's algorithm' named entity 'gray level' named entity 'DSC' named entity 'Otsu's method' named entity 'Gray level' named entity 'gray level' named entity 'Otsu's method' named entity 'Otsu's method' named entity 'entropy' named entity 'processed image' named entity 'workflow' named entity 'algorithm' named entity 'gray level' named entity 'entropy' named entity 'algorithm' named entity 'DSC' named entity 'salt-and-pepper noise' named entity 'probability' named entity 'Matlab' named entity 'histogram' named entity 'Otsu's method' named entity 'image enhancement' named entity 'gradient' named entity 'quantitative testing'

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