Vision-based hexagonal image processing using Hex-Gabor

Veni, S.; Narayanankutty, K.

doi:10.1007/s11760-012-0293-5

Cited by 15 publications

(10 citation statements)

References 24 publications

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“…It was observed that for σ value of 2/π we obtain better results while using Gabor bases in image processing [9], using this results in the Gabor Bases a minimum 3 dB bandwidth is observed. So, we use this value for implementation of the Modified Gabor transform in the NOFDM system.…”

Section: Implementation Of Nofdm Systemmentioning

confidence: 70%

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Spectrally Efficient Multi-Carrier Modulation Using Gabor Transform

Sriram¹,

Vijayakumar²,

Kumar³

et al. 2013

WET

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Non Orthogonal Frequency Division Multiplexing (NOFDM) systems make use of a transmission signal set which is not restricted to orthonormal bases unlike previous OFDM systems. The usage of non-orthogonal bases generally results in a trade-off between Bit Error Rate (BER) and receiver complexity. This paper studies the use of Gabor based on designing a Spectrally Efficient Multi-Carrier Modulation Scheme. Using Gabor Transform with a specific Gaussian envelope; we derive the expected BER-SNR performance. The spectral usage of such a NOFDM system when affected by a channel that imparts Additive White Gaussian Noise (AWGN) is estimated. We compare the obtained results with an OFDM system and observe that with comparable BER performance, this system gives a better spectral usage. The effect of window length on spectral usage is also analyzed.

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Section: Implementation Of Nofdm Systemmentioning

confidence: 70%

“…This implies that the bandwidth (B) used decreases with the window length i.e. B is proportional to N/p (9). From the plots (b) and (c) of Figure 5 we observe that the bandwidth used is almost the same but there is a decrease in the power of the out of band emissions.…”

Section: Simulation Results and Conclusionmentioning

confidence: 88%

Spectrally Efficient Multi-Carrier Modulation Using Gabor Transform

Sriram¹,

Vijayakumar²,

Kumar³

et al. 2013

WET

Self Cite

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“…At initial stages, Gaussian filter, Laplacian of Gaussian filter and Gabor filter are utilised to model photoreceptor cells, ganglion-horizontal cells and simple cells respectively. The utilisation of Hex-Gabor for efficient image enhancement is proposed by Veni and Narayanankutty (2012). An addressing scheme has also been proposed for general image processing applications such that the neighborhood information of each pixel are retained and saved in the memory for its processing.…”

Section: Introductionmentioning

confidence: 99%

Hardware implementation of hexagonal sampling based bio-inspired retinal encoder

Vinod

Veni

2017

IJSISE

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This paper addresses hardware implementation of a power efficient retinal encoder system used in visual prosthesis equipment for blind people. The hardware architecture is inspired from the retinal receptive fields in mammalian vision system. The captured image is passed through several filter banks in different filtering stages in primate vision system. As the photoreceptors in the primate vision system are arranged in hexagonal fashion, the hexagonal tessellation scheme was found to be the most suitable sampling scheme for retinal image processing. In this work, the hardware implementation of different retinal filtering stages and final edge detection scheme is performed in Altera Cyclone II FPGA and in Synopsys Design Vision. An area efficient Cellular Logic Array Processing (CLAP) algorithm is used as the final stage edge detector. Both rectangular and hexagonal edge detection schemes were tested and their performance was analysed using Berkeley Segmentation Dataset and ROC performance scheme.

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“…An overview of the advancements in edge detection techniques can be found in [10], including an approach of Canny edge detection on a hexagonal grid . Other edge detection methods on a hexagonal grid have been developed in [8], [29], [34], [35].…”

Section: Introductionmentioning

confidence: 99%

“…To date, research on processing hexagonal images includes areas such as image reconstruction [24], [37], hexagonal filter banks [21], [35], blue-noise halftoning [19], image segmentation [1], [2], [18] and facial recognition [25], [32]. Many edge detection algorithms that exist for conventional images are based on components strongly aligned with the horizontal and vertical axes, and hence they are not readily adaptable to a hexagonal lattice.…”

Section: Introductionmentioning

confidence: 99%

Multiscale Edge Detection using a Finite Element Framework for Hexagonal Pixel-based Images

Gardiner

Coleman

Scotney

2016

IEEE Trans. on Image Process.

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In recent years, the processing of hexagonal pixel-based images has been investigated, and as a result, a number of edge detection algorithms for direct application to such image structures have been developed. We build on this paper by presenting a novel and efficient approach to the design of hexagonal image processing operators using linear basis and test functions within the finite element framework. Development of these scalable first order and Laplacian operators using this approach presents a framework both for obtaining large-scale neighborhood operators in an efficient manner and for obtaining edge maps at different scales by efficient reuse of the seven-point linear operator. We evaluate the accuracy of these proposed operators and compare the algorithmic performance using the efficient linear approach with conventional operator convolution for generating edge maps at different scale levels.

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Vision-based hexagonal image processing using Hex-Gabor

Cited by 15 publications

References 24 publications

Spectrally Efficient Multi-Carrier Modulation Using Gabor Transform

Spectrally Efficient Multi-Carrier Modulation Using Gabor Transform

Hardware implementation of hexagonal sampling based bio-inspired retinal encoder

Multiscale Edge Detection using a Finite Element Framework for Hexagonal Pixel-based Images

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