Automatic parameter adjustment of difference of Gaussian (DoG) filter to improve OT-MACH filter performance for target recognition applications

Improving OT-MACH filter performance for target recognition applications with the use of a Rayleigh distribution filter

10.1117/12.918756 ◽

2012 ◽

Author(s):

Ahmad Alkandri ◽

Nagachetan Bangalore ◽

Akber Gardezi ◽

Philip Birch ◽

Rupert Young ◽

...

Keyword(s):

Target Recognition ◽

Rayleigh Distribution ◽

Filter Performance ◽

Mach Filter

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Scale Distorted Target Recognition Based on Machine Vision

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.1006-1007.760 ◽

2014 ◽

Vol 1006-1007 ◽

pp. 760-763 ◽

Cited By ~ 1

Author(s):

Yu Chen ◽

Fu Rong Huo ◽

Li Qin Zheng

Keyword(s):

Machine Vision ◽

Background Noise ◽

Target Recognition ◽

Angular Distortion ◽

Average Correlation ◽

Optical Correlation ◽

Hybrid Joint ◽

Mach Filter ◽

Human Eyes ◽

Principle Of Maximum

<div> Machine vision means to carry out measurement or judgment with machine instead of human eyes. In the field of target recognition, optical correlation technology is a main way to realize machine vision. Targets can be recognized and located with high precision taking advantage of optoelectronic hybrid joint transform correlator (OHJTC). However, when scale or angular distortion of the detected target exists relative to the reference template, the intensity of correlation peaks will decrease to a great extent, which restricted the recognition results greatly. In this paper, the development and principle of maximum average correlation height (MACH) algorithm is introduced. Through amounts of experiments, the controlling parameters of the synthesized filter are optimized, which makes MACH filter suppress background noise and widen recognition range of targets. To show the feasibility of this algorithm, simulative and optical experiments of the improved MACH filter are carried out. As an example, the recognition results of a fighter target in sky are given, which shows the scale distortion tolerance can reach up to ±23%. The actual effect of the improved MACH filter algorithm has been confirmed very well. <o:p></o:p> </div>

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Spatial Distorted Target Recognition Based on Improved Maximum Average Correlation Height Algorithm

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.602-605.1811 ◽

2014 ◽

Vol 602-605 ◽

pp. 1811-1814

Author(s):

Hong Zhi Liu ◽

Yu Chen ◽

Li Qin Zheng

Keyword(s):

Pattern Recognition ◽

Frequency Domain ◽

Experimental Analysis ◽

Background Noise ◽

Target Recognition ◽

Angular Distortion ◽

Joint Transform Correlator ◽

Average Correlation ◽

Different Shapes ◽

Mach Filter

Spatial distorted target is very hard to be recognized for complexity and variety of targets, which has restricted the development of pattern recognition technology to a great extent. Joint transform correlator is one of the key equipments to detect and recognize distorted targets. The appearance and development of maximum average correlation height (MACH) algorithm is introduced in this paper. Based on the principle the algorithm and experimental analysis, an improved maximum average correlation height algorithm fit for joint transform correlator is proposed, which has powerful capability of suppressing background noise and widening distortion tolerance. Target images with different shapes including scale or angular distortion constitute MACH filter in frequency domain, which is projected to space domain as reference template including varieties of attitude. To show the feasibility of the algorithm, an airplane with angular distortion in sky is processed by MACH filter as an example. Simulation and optical experimental results are given in this paper. The experiments show the angular distortion tolerance can reach up to 15 degrees. The actual effect of the improved MACH filter algorithm is confirmed very well.

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Optimization of OT-MACH filter generation for target recognition

10.1117/12.820950 ◽

2009 ◽

Cited By ~ 9

Author(s):

Oliver C. Johnson ◽

Weston Edens ◽

Thomas T. Lu ◽

Tien-Hsin Chao

Keyword(s):

Target Recognition ◽

Mach Filter

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Spatial distorted target recognition based on improved MACH filter

10.1117/12.2072504 ◽

2014 ◽

Author(s):

Yu Chen ◽

Furong Huo ◽

Liqin Zheng

Keyword(s):

Target Recognition ◽

Mach Filter

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Distorted target recognition based on canny operator enhancing OT-MACH filter

10.1117/12.999326 ◽

2012 ◽

Author(s):

Jiyang Shang ◽

Yu Zhang ◽

Qibo Zhang ◽

Wensheng Wang

Keyword(s):

Target Recognition ◽

Canny Operator ◽

Mach Filter

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Distorted Target Recognition Based on Prewitt Operator Combined with MACH Filter

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.552.523 ◽

2013 ◽

Vol 552 ◽

pp. 523-528

Author(s):

Ji Yang Shang ◽

Yu Zhang ◽

Qi Bo Zhang ◽

Wen Sheng Wang

Keyword(s):

Target Recognition ◽

Low Frequency ◽

Edge Extraction ◽

Tolerance Range ◽

Target Image ◽

Average Correlation ◽

Correlation Peak ◽

Training Images ◽

Mach Filter ◽

Frequency Domain Filtering

The distorted (scale and rotation etc.) target images and the training images are edge extracted by Prewitt operator. The Maximum Average Correlation Height filter is synthesized with the training images. The low frequency information of the distorted target images and the filter is enhanced. Then the edge extracted distorted target image is filtered by the Maximum Average correlation Height filter. Thereby, the distortion tolerance of the Maximum Average Correlation Height filter is expanded. By this method, when the space edge extraction combines with frequency domain filtering, the scale distortion tolerance is 0.76~1.56 times; the rotation distortion tolerance can reach up to 80 degrees. For the targets exceeding the distortion tolerance range, the intensity of correlation peak becomes weaker and weaker, but some of the targets can still be identified.

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