scholarly journals Efficient Optimal Multi-level Thresholding for Biofilm Image Segmentation

2009 ◽  
pp. 307-318 ◽  
Author(s):  
Darío Rojas ◽  
Luis Rueda ◽  
Homero Urrutia ◽  
Alioune Ngom
Keyword(s):  
Image Segmentation ◽  
Multi Level

Image segmentation of biofilm structures using optimal multi-level thresholding

2011 ◽  
Vol 5 (3) ◽  
pp. 266 ◽  
Author(s):  
Dario Rojas ◽  
Luis Rueda ◽  
Alioune Ngom ◽  
Homero Hurrutia ◽  
Gerardo Carcamo
Keyword(s):  
Image Segmentation ◽  
Multi Level

Cuckoo search with differential evolution mutation and Masi entropy for multi-level image segmentation

2021 ◽  
Author(s):  
Swarnajit Ray ◽  
Santanu Parai ◽  
Arunita Das ◽  
Krishna Gopal Dhal ◽  
Prabir Kumar Naskar
Keyword(s):  
Image Segmentation ◽  
Differential Evolution ◽  
Cuckoo Search ◽  
Multi Level ◽  
Masi Entropy

MULTI-LEVEL DOCUMENT IMAGE SEGMENTATION USING MULTI-LAYER PERCEPTRON AND SUPPORT VECTOR MACHINE

2012 ◽  
Vol 26 (06) ◽  
pp. 1253002 ◽  
Author(s):  
YAN ZHANG ◽  
BIN YU ◽  
HAI-MING GU
Keyword(s):  
Support Vector Machine ◽  
Image Segmentation ◽  
Research Area ◽  
Document Image ◽  
Support Vector ◽  
Multi Layer Perceptron ◽  
Document Image Analysis ◽  
Important Research Area ◽  
Multi Level ◽  
Document Image Segmentation

Document image segmentation is an important research area of document image analysis which classifies the contents of a document image into a set of text and non-text classes. Previous existing methods are often designed to classify text and halftone therefore they perform poorly in classifying graphics, tables and circuit, etc. In this paper, we present a robust multi-level classification method using multi-layer perceptron (MLP) and support vector machine (SVM) to segment the texts from non-texts and thereafter classify them as tables, graphics and halftones. This method outperforms previously existing methods by overcoming various issues associated with the complexity of document images. Experimental results prove the effectiveness of our proposed method. By virtue of our multi-level classification approach, the text components, halftone components, graphic components and table components are accurately classified respectively which would highly improve OCR accuracy to reduce garbage symbols as well as increase compression ratio thereafter simultaneously.

scholarly journals An Improved Marine Predators Algorithm With Fuzzy Entropy for Multi-Level Thresholding: Real World Example of COVID-19 CT Image Segmentation

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 125306-125330 ◽  
Author(s):  
Mohamed Abd Elaziz ◽  
Ahmed A. Ewees ◽  
Dalia Yousri ◽  
Husein S. Naji Alwerfali ◽  
Qamar A. Awad ◽  
...  
Keyword(s):  
Image Segmentation ◽  
Real World ◽  
Fuzzy Entropy ◽  
Ct Image ◽  
Marine Predators ◽  
Multi Level
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