Gray Scale Edge Detection using Interval-Valued Fuzzy Relations

Bouchet, Agustina; Quirós, Pelayo; Alonso, Pedro; Ballarin, Virginia L.; Dı́az, Irene; Montes, Susana

doi:10.1080/18756891.2015.1129588

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…(3) Select adaptive threshold When there is noise in the adaptive nonlinear diffusion image, the selection of lag threshold and filter size directly affects the image edge filtering effect. The large-size filter can reduce the noise and improve the image edge shape composite filtering effect by changing the filter size [14].…”

Section: T M mentioning

confidence: 99%

Analyzing scene image features with adaptive nonlinear diffusion equation filters for public safety project scheduling

Li¹,

You²,

2023

Preprint

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The current image feature detection methods fail to perform image edge filtering in all directions, leading to target deviation of the feature detection results, and narrower brightness level range of gray images. Hence, a novel approach based on adaptive nonlinear diffusion equation filtering is proposed for detecting security events in public safety project scheduling. An edge detection operator is developed that can work in any direction, and adaptive nonlinear diffusion image edge morphological composite filtering is implemented using lag threshold and NMS. The shape response of the image edge is calculated to select the adaptive threshold of feature extraction. A gaussian function pyramid is constructed to obtain the feature distribution sequence considering multi-scale factors. The wavelet analysis is used to analyze the gray scale and detail features of the scene images of public security events, and the gray projection method is utilized to detect the target features of dynamic images, completing the scene image feature detection of public security events. The experimental results demonstrate that the proposed feature detection method has high accuracy, shorter time, and ideal application performance.

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Section: T M mentioning

confidence: 99%

Analyzing scene image features with adaptive nonlinear diffusion equation filters for public safety project scheduling

Li¹,

You²,

2023

Preprint

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“…The results obtained using the new measure outperforms previous approaches. In [6] several Interval-Valued Fuzzy Sets construction methods for detecting edges in a gray scale image are proposed. These construction methods are based on considering information related to the neighborhood of each point.…”

Section: Related Workmentioning

confidence: 99%

Intuitionistic fuzzy set and fuzzy mathematical morphology applied to color leukocytes segmentation

Bouchet

Montes

Ballarin

et al. 2019

SIViP

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This work presents a new algorithm based on Atanassov's intuitionistic fuzzy sets and Fuzzy Mathematical Morphology to Leukocytes segmentation in color images. The main idea is based on modeling a color image as an Atanassov's intuitionistic fuzzy set using the hue component in the HSV color space. Then, a pixel labelled as leukocyte is selected and compared to the whole image with a similarity measure. Thus, the leukocyte is segmented and separated from the rest of the image. The experimental results show that the algorithm have a good performance, reaching a value of 99.41% for the correct classification of Leukocytes and a 99.23% for the correct classification of the background. Other metrics such as accuracy, precision and recall have been calculated obtaining 99.32%, 99.41% and 99.24%, respectively. The algorithm presents two important characteristics: It works directly over the color images without the need of converting the image in gray scale and it does not produce false colors because as Fuzzy Morphological operators guarantees it.

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“…Fuzzy Mathematical Morphology [5,44] is an extension of the Mathematical Morphology's binary operators to gray level images, by redefining the set operations as fuzzy set operations. In [7,8,9] we define the operators of the Fuzzy Mathematical Morphology for color images through the use of a fuzzy order. Other important works related to image processing are highlighted: In [16] information about spatial organization in an image is considered to improve object recognition and scene analysis tasks.…”

Section: Applicationsmentioning

confidence: 99%

Some Results and Applications Using Fuzzy Logic in Artificial Intelligence

Dı́az

Ralescu

et al. 2018

Studies in Systems, Decision and Control

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Algunas veces encuentras en la vida una amistad especial: ese alguien que al entrar en tu vida la cambia por completo. M. Benedetti, "Algunas amistades"Abstract In this chapter, several results and applications in artificial intelligence based on fuzzy logic are presented. We aim to highlight some recent works that are connected with the topic of this book, both in the theoretical and in the applied fields.

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Gray Scale Edge Detection using Interval-Valued Fuzzy Relations

Cited by 6 publications

References 15 publications

Analyzing scene image features with adaptive nonlinear diffusion equation filters for public safety project scheduling

Analyzing scene image features with adaptive nonlinear diffusion equation filters for public safety project scheduling

Intuitionistic fuzzy set and fuzzy mathematical morphology applied to color leukocytes segmentation

Some Results and Applications Using Fuzzy Logic in Artificial Intelligence

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