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Design and implementation of edge detection algorithm in dsPIC embedded processor

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conference contribution
posted on 2024-11-14, 11:17 authored by Prashan PremaratnePrashan Premaratne, Sabooh Ajaz, Ravi Monaragala, Nalin Bandara, Malin Premaratne
The research presented here is an attempt to use a very basic, low cost and non-specialized microcontroller for image processing tasks. The applications emanating from such an attempt will result in inexpensive face detection, intelligent motion sensors to low cost vehicle counting systems. We have been able to develop a system based on Microchip dsPIC microcontroller that implements edge detection of still images. Hardware-based signal processors such as Texas Instrument DSP (Digital Signal Processing) or Field Gate Arrays (FPGA) are generally an expensive solution for image processing applications. On the other hand a conventional 8-bit microcontroller doesn’t have enough capability to handle memory intensive DSP algorithms. In this regard, Microchip offers a tradeoff between cost and performance. Although performance does not compete with TI DSPs or FPGAs, the proposed system yet provides a sound platform to perform Signal processing directly on embedded hardware. Our research presents a preliminary approach to perform any type of image processing task using microchip 16-bit Microcontrollers and 16-bit digital signal controllers. Even though this attempt is aimed at Edge Detection, the research opens up possibilities for numerous other algorithms of signal and image processing that can be implemented using the same low cost hardware.

History

Citation

Premaratne, P., Ajaz, S., Monaragala, R., Bandara, N. & Premaratne, M. 2010, 'Design and implementation of edge detection algorithm in dsPIC embedded processor', in D. Dias (eds), ICIAFS 2010: 5th International Conference on Information and Automation for Sustainability, IEEE Computational Intelligence Society, Colombo, Sri Lanka, pp. 8-13.

Parent title

Proceedings of the 2010 5th International Conference on Information and Automation for Sustainability, ICIAfS 2010

Pagination

8-13

Language

English

RIS ID

35203

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