Search engine for discovering works of Art, research articles, and books related to Art and Culture
Javascript must be enabled to continue!
Optimal Cellular Automata Technique for Image Segmentation
View through CrossRef
Leukemia death secured 10 thplace among the most dangerous death in the world. The main reason is due to the delay in diagnosis which in turn delayed the treatment process. Hence it becomes an exigent requirement to diagnose leukemia in its early stage. Segmentation of WBC is the initial phase of leukemia detection using image processing.This paper aims to extract WBC from the image background. There exists various techniques for WBC segmentation in the literature. Yet, they provides inaccurate results.Cellular Automata can be effectively implemented in image processing. In this paper, we have proposed an Optimal Cellular Automata approach for image segmentation.In this approach, the optimal value for alive cells is obtained through particle swarm Optimization with Gravitational Search Algorithm (PSOGSA). The optimal value have fed in to the cellular automata model and get the segmented image. The results are validated based on the parameters likeRand Index (RI), Global Consistency Error (GCE), and Variation of Information (VOI). The Experimental results of proposed technique shows better results when compared to the previously proposed techniques namely, Hybrid K-Means with Cluster Center Estimation, Region Splitting and Clustering Technique and Cellular Automata. The proposed technique outperformed all other techniques.
Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP
Title: Optimal Cellular Automata Technique for Image Segmentation
Description:
Leukemia death secured 10 thplace among the most dangerous death in the world.
The main reason is due to the delay in diagnosis which in turn delayed the treatment process.
Hence it becomes an exigent requirement to diagnose leukemia in its early stage.
Segmentation of WBC is the initial phase of leukemia detection using image processing.
This paper aims to extract WBC from the image background.
There exists various techniques for WBC segmentation in the literature.
Yet, they provides inaccurate results.
Cellular Automata can be effectively implemented in image processing.
In this paper, we have proposed an Optimal Cellular Automata approach for image segmentation.
In this approach, the optimal value for alive cells is obtained through particle swarm Optimization with Gravitational Search Algorithm (PSOGSA).
The optimal value have fed in to the cellular automata model and get the segmented image.
The results are validated based on the parameters likeRand Index (RI), Global Consistency Error (GCE), and Variation of Information (VOI).
The Experimental results of proposed technique shows better results when compared to the previously proposed techniques namely, Hybrid K-Means with Cluster Center Estimation, Region Splitting and Clustering Technique and Cellular Automata.
The proposed technique outperformed all other techniques.
Related Results
PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA
PERBAIKAN CITRA INFRA MERAH DENGAN METODE CELLULAR AUTOMATA
Image enhancement is needed because not all images have good quality, such as noise, too low contrast or blurry image. These problems are commonly found in images generated from in...
AI‐enabled precise brain tumor segmentation by integrating Refinenet and contour‐constrained features in MRI images
AI‐enabled precise brain tumor segmentation by integrating Refinenet and contour‐constrained features in MRI images
AbstractBackgroundMedical image segmentation is a fundamental task in medical image analysis and has been widely applied in multiple medical fields. The latest transformer‐based de...
Multiple surface segmentation using novel deep learning and graph based methods
Multiple surface segmentation using novel deep learning and graph based methods
<p>The task of automatically segmenting 3-D surfaces representing object boundaries is important in quantitative analysis of volumetric images, which plays a vital role in nu...
Depth-aware salient object segmentation
Depth-aware salient object segmentation
Object segmentation is an important task which is widely employed in many computer vision applications such as object detection, tracking, recognition, and ret...
Review on 2D and 3D MRI Image Segmentation Techniques
Review on 2D and 3D MRI Image Segmentation Techniques
Background:
Magnetic Resonance Imaging is most widely used for early diagnosis
of abnormalities in human organs. Due to the technical advancement in digital image processing,
auto...
Leukemia Blood Cells Detection using Neural Network Classifier
Leukemia Blood Cells Detection using Neural Network Classifier
Image segmentation is an image processing operation performed on the image in order to partition the image into some images based on the information contained in the original image...
Сyberphysical representation of robots of the neuro-network collective of automata on a chip
Сyberphysical representation of robots of the neuro-network collective of automata on a chip
The article examines modern innovative technologies, which are a continuation, generalization of previously created technologies, deepening and expanding existing concepts, their a...
Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility
Two fully automated data-driven 3D whole-breast segmentation strategies in MRI for MR-based breast density using image registration and U-Net with a focus on reproducibility
AbstractPresence of higher breast density (BD) and persistence over time are risk factors for breast cancer. A quantitatively accurate and highly reproducible BD measure that relie...