Remember Me
Or use your Academic/Social account:


Or use your Academic/Social account:


You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.


Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message


Verify Password:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Gibson, R.M.; Ahmadinia, A.; McMeekin, S.G.; Strang, N.C.; Morison, G. (2013)
Publisher: Springer
Languages: English
Types: Article

Classified by OpenAIRE into

There is a significant number of visually impaired individuals who suffer sensitivity loss to high spatial frequencies, for whom current optical devices are limited in degree of visual aid and practical application. Digital image and video processing offers a variety of effective visual enhancement methods that can be utilised to obtain a practical augmented vision head-mounted display device. The high spatial frequencies of an image can be extracted by edge detection techniques and overlaid on top of the original image to improve visual perception among the visually impaired. Augmented visual aid devices require highly user-customisable algorithm designs for subjective configuration per task, where current digital image processing visual aids offer very little user-configurable options. This paper presents a highly user-reconfigurable morphological edge enhancement system on field-programmable gate array, where the morphological, internal and external edge gradients can be selected from the presented architecture with specified edge thickness and magnitude. In addition, the morphology architecture supports reconfigurable shape structuring elements and configurable morphological operations. The proposed morphology-based visual enhancement system introduces a high degree of user flexibility in addition to meeting real-time constraints capable of obtaining 93 fps for high-definition image resolution.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 1. S Resnikoff, D Pascolini, D Etya'ale, I Kocur, R Pararajasegaram, GP Pokharel, SP Miariotti, Global data on visual impairment in the year. World Health Org. 82, 844-851 (2004)
    • 2. C Verarrt, F Duret, M Brelen, M Oozer, J Delbeke, Vision rehabilitation in the case of blindness. Expert Rev. Med. Devices 1(1), 139-153 (2004)
    • 3. SE Hassan, JE Lovie-Kitchin, RL Woods, Vision and mobility performance of subjects with age-related macular degeneration. Optom. Vis. Sci. 79(11), 697-707 (2002)
    • 4. CM Dickinson, V Fotinakis, The limitations imposed on reading by low vision aids. Optom. Vis. Sci. 77(7), 364-372 (2000)
    • 5. LM Watson, NC Strang, F Scobie, GD Love, D Seidel, V Manahilov, Image jitter enhances visual performance when spatial resolution is impaired. Invest. Ophthalmol. Vis. Sci. 53(10), 6004-6010 (2012)
    • 6. JS Wolffsohn, D Mukhopadhyay, M Rubinstein, Image enhancement of real-time television to benefit the visually impaired. Am. J. Ophthalmol. 144(3), 436-440 (2007)
    • 7. J Serra, Image Analysis and Mathematical Morphology, vol. I (Academic, London, 1982)
    • 8. E Peli, J Kim, Y Yitzhaky, RB Goldstein, RL Woods, Wide-band enhancement of television images for people with visual-impairments. J. Opt. Soc. Am. A 21(6), 937-950 (2004)
    • 9. E Peli, G Luo, A Bowers, N Rensing, Development and evaluation of vision multiplexing devices for vision impairment. Int. J. Artif. Intell. T. 18(3), 365-378 (2009)
    • 10. G Luo, P Satgunam, E Peli, Visual search performance of patients with vision impairment: effect of JPEG image enhancement. Ophthalmic Physiol. Opt. 32, 421-428 (2012)
    • 11. M Fullerton, RL Woods, FA Vera-Diaz, E Peli, Measuring perceived video quality of MPEG enhancement by people with impaired vision. J. Opt. Soc. Am. A 24(12), B174-B187 (2007)
    • 12. P Satgunam, RL Woods, G Luo, PM Bronstad, Z Reynolds, C Ramachandra, BW Mel, E Peli, Effects of contour enhancement on low-vision preference and visual search. Optom. Vis. Sci. 89(9), 1364-1373 (2012)
    • 13. G Luo, E Peli, Use of an augmented-vision device for visual search in patients with tunnel vision. Invest. Ophthalmol. Vis. Sci. 47(9), 4152-4159 (2006)
    • 14. W Atabany, P Degenaar, A robust edge enhancement approach for low vision patients using scene simplification (Paper presented at the Cairo international biomedical engineering conference, Cairo, 2008), pp. 18-20
    • 15. W Al-Atabany, MA Memon, SM Downes, P Degenaar, Designing and testing scene enhancement algorithms for patients with retina degenerative disorders. Biomed. Eng. Online 9, 27 (2010)
    • 16. RM Gibson, SG McMeekin, A Ahmadinia, NC Strang, G Morison, Optimal edge detection for a real-time head mounted display providing low vision aid (Paper presented at the 2nd IASTED international conference on assistive technologies, Innsbruck, 2012), pp. 15-17
    • 17. H Winnemöller, SC Olsen, B Gooch, Real-time video abstraction. ACM T. 25(3), 1221-1226 (2006)
    • 18. B Saha, B Bhowmick, A Sinha, An embedded solution for visually impaired (Paper presented at the IEEE 13th international symposium on consumer electronics, Kyoto, 2009), pp. 467-471
    • 19. E Ros, J Diaz, S Mota, F Vargas-Martin, MD Pelaez-Coca, Real time image processing on a portable aid device for low vision patients, in Reconfigurable Computing: Architectures and Applications, Lecture Notes in Computer Science, 3985 (Springer, Berlin/Heidelberg, 2006), pp. 158-163
    • 20. RM Gibson, SG McMeekin, A Ahmadinia, NC Strang, G Morison, Evaluation of visual aid enhancement algorithms for real-time embedded systems (Paper presented at the IEEE 9th international conference on embedded software and systems, Liverpool, 2012), pp. 1762-1769
    • 21. S Marshall, Logic-based Nonlinear Image Processing (SPIE Society of PhotoOptical, Bellingham, WA, 2006)
    • 22. S Marshall, GL Sicuranza, Advances in nonlinear signal and image processing (EURASIP Book Series on Signal Processing & Communications Pt. 6 (Hindawi Publishing Corporation, New York, NY, 2006)
    • 23. TA Mahmoud, S Marshall, Medical image enhancement using threshold decomposition driven adaptive morphological filter (Paper presented at the 16th European Signal Processing Conference, Lausanne, 2008), pp. 25-29
    • 24. TA Mahmoud, S Marshall, Edge-detected guided morphological filter for image sharpening. EURASIP J. Proc. 2008(970353), 1-9 (2008)
    • 25. M Holzer, F Schumacher, T Greiner, W Rosenstiel, Optimized hardware architecture of a smart camera with novel cyclic image line storage structures for morphological raster scan image processing. Paper presented at the IEEE int. conf. emerg. sig. proc. appl. L V. NV. 12-14, 83-86 (January 2012)
    • 26. M Kraft, K Andrzej, Morphological edge detection algorithm and its hardware implementation. Com. Recog. Sys. 2, 132-139 (2007)
    • 27. S Fejes, F Vajda, A data-driven algorithm and systolic architecture for image morphology. Paper presented at the IEEE int. conf. proc. 2, 550-554 (1994). Austin, TX, 13-16 November
    • 28. H Hedberg, F Kristensen, P Nilsson, V Owall, A low complexity architecture for binary image erosion and dilation using structuring element decomposition. Paper presented at the IEEE international symposium on Circuits and Sys. 4, 3431-3434 (2005)
    • 29. O Déforges, N Normand, M Babel, Fast recursive grayscale morphology operators: from the algorithm to the pipeline architecture. J. of Real-Time Image Proc. 5(3), 1-10 (2010)
    • 30. SY Chien, SY Ma, LG Chen, Partial-result-reuse architecture and its design technique for morphological operations with flat structuring elements. Circuits and Systems for Video Tech. IEEE Trans. 15(9), 1156-1169 (2005)
    • 31. J Bartovsky, E Dokladalova, P Dokladal, V Georgiev, Pipeline architecture for compound morphological operators (Paper presented at the 17th IEEE international conference on image processing, Hongkong, 2010), p. 3768
    • 32. J Bartovský, P Dokládal, E Dokládalová, V Georgiev, Parallel implementation of sequential morphological filters. J. of Real-Time Image Proc. , 1-13 (2011). doi:10.1007/s11554-011-0226-5
    • 33. J Kasperek, Real time morphological image contrast enhancement in virtex FPGA (Berlin/Heidelberg, Field-Programmable Logic and Applications (Springer, 2001), pp. 430-440
    • 34. M Genovese, E Napoli, FPGA-based architecture for real time segmentation and denoising of HD video. J. of Real-Time Image Proc. , 1-13 (2011). doi:10.1007/s11554-011-0238-1
  • No related research data.
  • No similar publications.

Share - Bookmark

Download from

Cite this article