Nature Inspired Optimization Techniques for Image Processing—A Short Review

2018 ◽  
pp. 113-145 ◽  
Author(s):  
S. R. Jino Ramson ◽  
K. Lova Raju ◽  
S. Vishnu ◽  
Theodoros Anagnostopoulos
Keyword(s):  
Image Processing ◽  
Short Review ◽  
Optimization Techniques

Computational Intelligence-Based Cell Nuclei Segmentation from Pap Smear Images

2016 ◽  
pp. 262-284
Author(s):  
Savitha Balakrishnan ◽  
Subashini Parthasarathy ◽  
Krishnaveni Marimuthu
Keyword(s):  
Image Processing ◽  
Cervical Cancer ◽  
Computational Intelligence ◽  
Pap Smear ◽  
Correct Diagnosis ◽  
Optimization Techniques ◽  
Cell Nuclei ◽  
Swarm Optimization ◽  
Nuclei Segmentation ◽  
Segmentation Problem

Automated Segmentation of cell nuclei in Pap smear images plays an important role in the cervical cancer cell analysis systems to make a correct diagnosis decision. The aim of this chapter is to detail about the variety of computational intelligence and image processing approaches developed and used for the nuclei segmentation. In additional, the threshold based segmentation problem is treated as an optimization problem with an objective of preserving both the size and volume of the cell nuclei and also to segment the nuclei region from the original microscopic Pap smear image with the help of Particle Swarm Optimization (PSO) and Ant Colony Optimization techniques (ACO). Experimental results are shown, compared in quantitative and qualitative manner as well as the main advantages and limitations of each algorithm are explained.

A Combinatory Design Methodology Dedicated to the Ball and Roller Screw Drives for Optimum Design

2010 ◽  
Author(s):  
Pierre Dupont
Keyword(s):  
Optimum Design ◽  
Design Methodology ◽  
Short Review ◽  
Optimization Techniques ◽  
Industrial Case Study ◽  
Endurance Strength ◽  
Memorial Symposium ◽  
Roller Screw ◽  
The One ◽  
User Friendly

Machine-tools, packaging units, lifting systems and also other heavy duty devices (f.e. used in steel casting technologies) employ advantageously screw drives (balls, re-circulating rollers, and planetary roller drives) as mechanical command elements (f.e. directly coupled to servo drives), especially for their high efficiencies (∼87 .. 98%) and “output force to input torque ratio”. After a short review of the most important checks (for Static and Endurance Strength, Life, Shocks resistance and also some Miscellaneous Effects due f.e. to Critical Speeds and Stress Concentrators) it will be described briefly a combinatory design methodology or “heuristics” which takes into account as the technical viability and reliability as well as the economical feasibility of the whole system line (included end bearings and transmission) leading to an “overall safety ratio matrix” and/or to “viability and reliability graphs” helping in such a way the designer to reach an “optimum design” by an overall helicopter view of his/her design(s). In terms of optimization techniques, this user friendly combinatory design methodology could be placed in the field of the “heuristic” ones. An industrial case study will illustrate that presentation. This presentation is also a continuation of the one given for the MS&T’09 occurring in PITTSBURGH, USA during the “Charles R. MORIN Memorial Symposium on Failure Analysis & Prevention” for the ASM International.

Computational Intelligence-Based Cell Nuclei Segmentation from Pap Smear Images

Biometrics ◽  
2017 ◽  
pp. 259-280
Author(s):  
Savitha Balakrishnan ◽  
Subashini Parthasarathy ◽  
Krishnaveni Marimuthu
Keyword(s):  
Image Processing ◽  
Cervical Cancer ◽  
Computational Intelligence ◽  
Pap Smear ◽  
Correct Diagnosis ◽  
Optimization Techniques ◽  
Cell Nuclei ◽  
Swarm Optimization ◽  
Nuclei Segmentation ◽  
Segmentation Problem

Automated Segmentation of cell nuclei in Pap smear images plays an important role in the cervical cancer cell analysis systems to make a correct diagnosis decision. The aim of this chapter is to detail about the variety of computational intelligence and image processing approaches developed and used for the nuclei segmentation. In additional, the threshold based segmentation problem is treated as an optimization problem with an objective of preserving both the size and volume of the cell nuclei and also to segment the nuclei region from the original microscopic Pap smear image with the help of Particle Swarm Optimization (PSO) and Ant Colony Optimization techniques (ACO). Experimental results are shown, compared in quantitative and qualitative manner as well as the main advantages and limitations of each algorithm are explained.

scholarly journals Brain Tumor Detection by using Fcm Algorithm

2020 ◽  
Vol 9 (4) ◽  
pp. 1856-1862
Keyword(s):  
Image Processing ◽  
Input Image ◽  
Contour Detection ◽  
Optimization Techniques ◽  
Video Frame ◽  
Image Process ◽  
Core Analysis ◽  
Accuracy Level ◽  
Process System ◽  
Processing Techniques

capable of changing a picture into digital type and it perform operations on image. In image process, input is a picture (may be a video frame or a photograph in any format) and therefore the output is also a picture or the characteristics of the input image. Image process system sometimes considers a picture as a 2 dimensional signal, whereas process. It’s one in all the rising technologies, with its branches of application widespread into many domains of business. Image process may be a core analysis in space engineering and it additionally acts as a thrust space in alternative disciplines of applied science. Researchers would like to do perform research in image processing; because it offers real time applications and therefore the results derived from image processing techniques are created. In this paper we have discussed about the greedy snake segmentation, snake contour detection and fcm optimization techniques for segmenting the tumor image, the accuracy level is increased up to 90% compared with the existing algorithm.

Implementation of Intelligent Video Analysis System and it’s Algorithm Optimization Based on DSP

2011 ◽  
Vol 403-408 ◽  
pp. 217-222
Author(s):  
Hui Wang ◽  
Cheng Wu Liang ◽  
Ying Li
Keyword(s):  
Image Processing ◽  
Video Analysis ◽  
Digital Signal Processor ◽  
Digital Signal ◽  
Optimization Techniques ◽  
Algorithm Optimization ◽  
Automatic Tracking ◽  
Analog Channels ◽  
Analysis System ◽  
Algorithm Level

This paper aims to implement an distributed intelligent video analysis system based on TI multimedia Digital Signal Processor (DSP) TMS320DM642, at the same time, the algorithm optimization is also described. The intelligent video analysis system we proposed provides users with fast and precise video analysis services. The video image is transmitted to the image processing board by analog channels and IP cameras, then the DSP processing the video flow. In this system, target detection, segmentation, feature extraction, alarm and automatic tracking can be implemented. In this system, several optimization techniques are also used in algorithms, including the algorithm level optimization (ALO), the program level optimization (PLO) and the instruction level optimization (ILO). Experimental results show the exellent result in reducing the CPU load.

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