Wavelet-modified fringe-adjusted joint transform correlator

Bhagatji, Alpana; Nishchal, Naveen K.; Gupta, A.; Tyagi, B. P.

doi:10.1016/j.optlastec.2007.03.007

Cited by 14 publications

(1 citation statement)

References 26 publications

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“…The majority of the existing methods [7][8][9] for pattern recognition through optical correlation happen to be developed for 2D objects, which may have played important roles in several applications for instance detection, recognition, and classifying with the images. Nevertheless the intensity shapes from those algorithms only support the gray scale data, and lose the peak distribution information belonging to the object.…”

Section: Introductionmentioning

confidence: 99%

Similarity Measure Using Hausdorff Distance in 2D Shape Recognition System

Enayatifar¹,

Salam²

2013

Proceedings of the 2nd International Symposium on Computer, Communication, Control and Automation

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Abstract-Shape plays an important role for human to recognize an object. Shape can be recognized easily by human regardless of size, rotation or translation. In this paper a shape recognition system is presented. In this research, authors investigate late improves in shape analysis and shape recognition issues with a concentrate on significant highlights of a shape. In the proposed method, the first stage is an edge detection method based on fuzzy cellular automata. In the second stage, shapes were clustered based on the differences of degree of each angle. Finally Hausdorff method is used for determining the rate of similarities. Simulation results demonstrate the system invariance to rotation, translation and scale.

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Section: Introductionmentioning

confidence: 99%