Log-polar transform-based wavelet-modified maximum average correlation height filter for distortion-invariant target recognition

Aran, Amit; Nishchal, Naveen K.; Beri, Vinod K.; Gupta, A.

doi:10.1016/j.optlaseng.2007.07.006

Cited by 11 publications

(4 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The dataset was divided into two classes: true class (car1) and false class (car2 and car3) images, as shown in Figure 1i-iii. We implemented the synthesized WEMACH in a hybrid optical-correlator scheme [10,11,[18][19][20][21]. In this geometry, the target image is Fourier-transformed and multiplied with the pre-synthesized filter, which is referred to as a product function.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In this geometry, the target image is Fourier-transformed and multiplied with the pre-synthesized filter, which is referred to as a product function. The Fourier We implemented the synthesized WEMACH in a hybrid optical-correlator scheme [10,11,[18][19][20][21]. In this geometry, the target image is Fourier-transformed and multiplied with the pre-synthesized filter, which is referred to as a product function.…”

Section: Simulation Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Improving the False Alarm Capability of the Extended Maximum Average Correlation Height Filter

Kumar,

Nishchal,

Alfalou

2023

Photonics

Self Cite

View full text Add to dashboard Cite

The extended maximum average correlation height (EMACH) filter is a potent pattern-detection tool used in image processing and computer vision applications. This filter enhances the effectiveness of the maximum average correlation height (MACH) filter by adding more features and flexibility. Incorporating the benefits of wavelet decomposition, we updated the EMACH filter to enhance its performance. The updated filter offered improved accuracy, robustness, and flexibility in recognizing complex patterns and objects in images with varying lighting conditions, noise levels, and occlusions. To verify the results’ consistency and compare their performance with that of the MACH filter and EMACH filter, performance metrics like peak-to-correlation energy, peak-to-sidelobe ratio, signal-to-noise ratio, and discrimination ratio were computed. Through numerical and experimental studies, we found that the proposed filter enhances the identification rate and decreases the number of false alarms.

show abstract

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Improving the False Alarm Capability of the Extended Maximum Average Correlation Height Filter

Kumar,

Nishchal,

Alfalou

2023

Photonics

Self Cite

View full text Add to dashboard Cite

show abstract

“…The transformation given in (26) amounts to subtraction of a blurred version of the image from a less blurred version of the same. Both blurred versions are acquired as an outcome of convolution process involving the original grey-scale image and Gaussian kernels with different standard deviations.…”

Section: Preprocessing Stage A: Dog-based Enhancementmentioning

confidence: 99%

“…Since then multiple variants including extended MACH (EMACH) [21] and eigen-EMACH (E 2 MACH) [22] have been proposed with respective improvements as well as trade-offs [23]. Most recently some hybrid filtering strategies based on wavelets (WMACH) [24,25] and logarithmic mapping transformations [logarithmically MACH (LMACH)/LEMACH] [26][27][28] have also been proposed to cater for additional problems of in-plane and out-of-plane rotations as well as scale variations.…”

Section: Introductionmentioning

confidence: 99%