Image segmentation is one of the pivotal steps in image processing. Actually, it deals with the partitioning of the image into different classes based on pixel intensities. This work …
EH Houssein, MM Emam, AA Ali - Neural Computing and Applications, 2021 - Springer
Abstract Coronavirus disease 2019 (COVID-19) is pervasive worldwide, posing a high risk to people's safety and health. Many algorithms were developed to identify COVID-19. One way …
AK Bhandari - Neural computing and applications, 2020 - Springer
Multilevel thresholding for image segmentation is a crucial process in several applications such as feature extraction and pattern recognition. The meticulous search for the best values …
Image segmentation is necessity of many application like brain tumor detection, optical character recognition, thermal energy leakage detection, Face recognition etc. multilevel …
Among various thresholding methods, minimum cross entropy is implemented for its effectiveness and simplicity. Although it is efficient and gives excellent result in case of bi …
This paper presents a multi-level image thresholding approach based on fuzzy partition of the image histogram and entropy theory. Here a fuzzy entropy based approach is adopted in …
Segmentation of image is a key step in image analysis and pre-processing. It consists of separating the pixels into different segments based on their intensity level according to …
The data explosion caused by the Internet and its applications has given researchers immense scope for data analysis. A large amount of data is available in form of images …
Z Yang, A Wu - Neural Computing and Applications, 2020 - Springer
Multilevel thresholding for image segmentation is one of the crucial techniques in image processing. Even though numerous methods have been proposed in literature, it is still a …