Recent advances in harris hawks optimization: A comparative study and applications

AG Hussien, L Abualigah, R Abu Zitar, FA Hashim… - Electronics, 2022 - mdpi.com
The Harris hawk optimizer is a recent population-based metaheuristics algorithm that
simulates the hunting behavior of hawks. This swarm-based optimizer performs the …

[PDF][PDF] A survey: Image segmentation techniques

MW Khan - International Journal of Future Computer and …, 2014 - researchgate.net
Segmentation is considered as one of the main steps in image processing. It divides a digital
image into multiple regions in order to analyze them. It is also used to distinguish different …

Reversible data hiding with contrast enhancement and tamper localization for medical images

G Gao, X Wan, S Yao, Z Cui, C Zhou, X Sun - Information Sciences, 2017 - Elsevier
Digital transmission of medical images often involves hiding crucial information in some
parts of the images which should be later extracted to authenticate ownership and identity. In …

Brain tumour segmentation using S-Net and SA-Net

S Roy, R Saha, S Sarkar, R Mehera, RK Pal… - IEEE …, 2023 - ieeexplore.ieee.org
Image segmentation is an application area of computer vision and digital image processing
that partitions a digital image into multiple image regions or segments. This process involves …

Active contour driven by multi-scale local binary fitting and Kullback-Leibler divergence for image segmentation

L Liu, D Cheng, F Tian, D Shi, R Wu - Multimedia Tools and Applications, 2017 - Springer
Image segmentation is an important processing in many applications such as image
retrieval and computer vision. One of the most successful models for image segmentation is …

[PDF][PDF] An efficient image segmentation method based on linear discriminant analysis and K-means algorithm with automatically splitting and merging clusters

S Mia, MM Rahman - International Journal of Imaging and …, 2018 - researchgate.net
Image segmentation plays a significant role in image processing, pattern recognition and as
well as in computer vision. It aims to classify the meaningful objects residing in the image …

Sparse graph connectivity for image segmentation

X Zhu, S Zhang, J Zhang, Y Li, G Lu… - ACM Transactions on …, 2020 - dl.acm.org
It has been demonstrated that the segmentation performance is highly dependent on both
subspace preservation and graph connectivity. In the literature, the full connectivity method …

[PDF][PDF] Segmentation and measurement of medical image quality using K-means clustering algorithm

AMA Karrar, J Sun - American Journal of Neural Networks and …, 2019 - academia.edu
In this paper we have segmented an image by using a k-clustering algorithm, using the
Gaussian Mixture Model cluster to generate the initial centroid. Many types of research have …

Image Segmentation Techniques: A Survey

S Puri, S Singh - International Journal of Engineering and Applied …, 2021 - ijeap.org
Segmenting an image utilizing diverse strategies is the primary technique of Image
Processing. The technique is broadly utilized in clinical image handling, face …

[PDF][PDF] A SURVEY ON BRAIN TUMOR IDENTIFICATION THROUGH MEDICAL IMAGES.

M Saini, S Saini, P Tripathi, KK Saini… - International Journal of …, 2017 - academia.edu
This paper presents a survey on the detection of brain tumor. Brain Tumor can be described
as a cluster of abnormal cells which grows inside the brain by uncontrolled growth in tissues …