Edge detection image using ARM microcontroller

Article Sidebar

PDF (Spanish) HTML (Spanish)
Published: 2016-10-31
DOI: https://doi.org/10.17163/ings.n16.2016.04
Keywords:
ARM, edge detection, digital image processing, Sobel Filter

Main Article Content

Juan Francisco Ordoñez
http://orcid.org/0000-0002-8770-550X
Luis Oñate
http://orcid.org/0000-0002-1323-1858

Abstract

In this document is described as an image edge detector was developed, this technique is useful in a wide range of applications such as metrology, face recognition, pattern detection because it determines the border between two regions with different characteristics. the development board STM32FI-DISC was used, although this microcontroller is not designed for digital image processing (PDI) as microcontrollers Texas Instruments, Analog Device, etc. has a speed high processing and uses 32-bit program. The edge detector module uses the ARM microcontroller STmicroelectronics adding a camera to take pictures and is presented on a display thin film transistor (TFT) image where the edge detector was applied using the Sobel filter to determine movement object by a difference images. In addition, the detector implemented in Matlab filter edges and the images analyzed with the Matlab software and obtained the development board finding its likeness, being the images with a high degree of similarity buildings, geometric figures and printed circuits compared. Thus it was possible to apply an edge detection algorithm on this hardware at low cost.

Article Details

Issue
No. 16 (2016): July / December
Section
Scientific Paper

 

The Universidad Politécnica Salesiana of Ecuador preserves the copyrights of the published works and will favor the reuse of the works. The works are published in the electronic edition of the journal under a Creative Commons Attribution/Noncommercial-No Derivative Works 4.0 Ecuador license: they can be copied, used, disseminated, transmitted and publicly displayed.

The undersigned author partially transfers the copyrights of this work to the Universidad Politécnica Salesiana of Ecuador for printed editions.

It is also stated that they have respected the ethical principles of research and are free from any conflict of interest. The author(s) certify that this work has not been published, nor is it under consideration for publication in any other journal or editorial work.

The author (s) are responsible for their content and have contributed to the conception, design and completion of the work, analysis and interpretation of data, and to have participated in the writing of the text and its revisions, as well as in the approval of the version which is finally referred to as an attachment.

References

[1] G. Anusha, J. T y N. Satya, «Implementation of SOBEL Edge Detection,» International Journal of Computer Trends and Technology, vol. 3, nº 3, pp. 472-475, 2012.

[2] S. Ravi, A. Rahim y F. Shaik, «FPGA Based Design and Implementation of Image Edge Detection Using Xilinx System Generator,» International Journal of Engineering Trends and Technology, vol. 4, nº 10, pp. 4657-4660, 2013.

[3] P. Premaratne, Ajaz, Monaragala, Bandara y M. Premaratne, «Design and Implementation of Edge Detection,» de 2010 Fifth International Conference on Information and Automation for Sustainability , Colombo, 2010.

[4] L. Tan, Digital Signal Processing Fundamentals and Applications, Academic Press, 2013.

[5] STMicroelectronics, «STMicroelectronics,» [En línea]. Available: http://www2.st.com/content/ccc/resource/technical/document/datasheet/03/b4/b2/36/4c/72/49/29/DM00071990.pdf/files/DM00071990.pdf/jcr:content/translations/en.DM00071990.pdf. [Último acceso: 23 Abril 2016].

[6] S. Pratibha, M. Diwakar y C. Sangam, «Application of Edge Detection for Brain,» International Journal of Computer Applications, vol. 58, nº 16, pp. 21-25, 2012.

[7] M. Anupam y K. Debaditya, «Motion analysis in video surveillance using edge detection,» IOSR Journal of Computer Engineering, vol. 12, nº 6, pp. 10-15, 2013.

[8] Y. Ramadevi, T. Sridevi, B. Poornima y B. Kalyani, «Segmentation and Object Recognition using edge detection techniques,» International Journal of Computer Science & Information Technology(IJCSIT), vol. 2, nº 6, pp. 153-161, 2010.

[9] U. Sefercik y O. Gulegen, «Edge Detection in Geologic Formation Extraction: Close Range and Remote Sensing Case Studies,» 2012.

[10] N. Singh, D. Gandhi y K. P. Singh, « Recognition System Using a Canny Edge Detection and a Circular Hough Transform,» International Journal of Advances in Engineering & Technology, vol. 1, nº 2, pp. 221-228, 2011.

[11] Omnivision, «datasheet OV7670,» [En línea]. Available: http://www.voti.nl/docs/OV7670.pdf. [Último acceso: 23 abril 2016].

[12] R. Green y M. Zechner, Beginning Android Games, New York: Apress, 2012, pp. 89-91.

[13] STMicroelectronics, «STM32F series,» Abril 2016. [En línea]. Available: http://www2.st.com/content/st_com/en/products/microcontrollers/stm32-32-bit-arm-cortex-mcus/stm32f3-series.html. [Último acceso: Abril 2016].

[14] Wide, «2.4” QVGA (320x240) TFT-LCD,» [En línea]. Available: http://www.wide.hk/pdf/240320.pdf. [Último acceso: 23 abril 2016].

[15] S. Labs, «CP2102,» [En línea]. Available: https://www.silabs.com/Support%20Documents/TechnicalDocs/CP2102-9.pdf. [Último acceso: 23 Abril 2016].

[16] C. Solomon y T. Breckon, Fundamentals of Digital Image Processing, Oxford: Wiley-Blackwell, 2011, pp. 97-103.

[17] L. Shapiro y G. Stockman, Computer Vision, New Jersey: Prentice-Hall, 2001, pp. 156-166.

[18] S. Jayaraman, Digital Imagen Processing, New Delhi: Tata McGraw Hill, 2009, pp. 127-132.