Improved thresholding based on negative selection algorithm (NSA)

Mahapatra, Prasant Kumar; Kaur, Mandeep; Sethi, Spardha; Thareja, Rishabh; Kumar, Amod; Devi, Swapna

doi:10.1007/s12065-013-0089-8

Cited by 7 publications

(3 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The errors can be reduced further using different bio-inspired computing techniques and its hybridization such as particle swarm optimization (PSO) and AIS. 29 The algorithms for image thresholding, 27 enhancement, 30 and error optimization may be incorporated in this developed GUI in future for more accurate tool positioning.…”

Section: Discussionmentioning

confidence: 99%

“…These images were then enhanced and segmented using sobel edge detection and NSA-based thresholding. 27…”

Section: Methodsmentioning

confidence: 99%

“…These images were then enhanced and segmented using sobel edge detection and NSAbased thresholding. 27 NSA is a bio-inspired technique used for thresholding process derived from Artificial Immune System (AIS). The process of thresholding based on NSA is explained as follows.…”

Section: Algorithm For Determination Of Known Position Of Tool and Ermentioning

confidence: 99%

See 2 more Smart Citations

A Machine Vision System for Tool Positioning and Its Verification

Mahapatra

Thareja

Kaur

et al. 2015

Measurement and Control

Self Cite

View full text Add to dashboard Cite

This paper presents a machine vision–based precise tool positioning and verification system that may be used with milling and lathe machines, and so on. For many industrial applications, the accuracy required in machining operations is of the order of microns. The developed machine vision–based tool position verification process involves pixel calibration to compute and measure real-world minute dimensions. These measurements are based on two-dimensional spatial correlation of sequential images captured from the movement of the tool with a resolution of 250 µm. The captured sequential images are thresholded using a new bio-inspired technique named Negative Selection Algorithm, a model of Artificial Immune System. The developed system extracts the difference between the actual and target positions of the tool from the captured images through image processing and calculates the error. To compensate for the positional error, alignment commands are fed to the two-axis high precision motor. The maximum error observed was ±206 µm for 14.99999 mm movement.

show abstract

Section: Discussionmentioning

confidence: 99%

“…These images were then enhanced and segmented using sobel edge detection and NSA-based thresholding. 27…”

Section: Methodsmentioning

confidence: 99%