Image Enhancement and Edge Detection for Real Time System Applications
Abstract
With development in technology, medicine has been greatly benefited and new avenues for research opened up, one such field being the real time medical image processing whose applications have allowed medical practitioners worldwide to better diagnosis abilities. It consists of the implementation of various image processing algorithms like edge detection using mask filters, edge enhancement, interpolation etc resulting in better images suitable for diagnosis. The algorithmic computations in real-time may have high level of time based complexity and hence the use of digital signal processors (DSPs) for the implementation of such algorithms is proposed here. We employed TI 320 DM642 DSP for the purpose of image enhancement and edge detection purposes in our work. The problem required us to develop algorithms that are time and memory efficient and worked in agreement with real time specifications. This application desires that the DSPs be highly computationally efficient while working on low power. We thus discuss further the approach we followed while working on the above said platform and its applications in the field of medical research.
1. Introduction Real time medical imaging in todays world has become a field which requires ultra high speed processing. In order to satisfy this we have inculcated image processing algorithms on TI 320 DM642 DSP processor where the source of images has been considered from BOSCH camera and Sonline Adara Ultrasound Image system. Medical images enhancement and edge detection is an important work for object recognition of the human organs and it is an essential pre-processing requirement in medical imaging. The effect of the edge detection decides the result of the final processed image. Conventionally, edge is detected according to some early brought forward algorithms like Sobel algorithm, Canny algorithm and Laplacian of Gaussian operator(zero crossing method in our case) , but in theory they belong to
With development in technology, medicine has been greatly benefited and new avenues for research opened up, one such field being the real time medical image processing whose applications have allowed medical practitioners worldwide to better diagnosis abilities. It consists of the implementation of various image processing algorithms like edge detection using mask filters, edge enhancement, interpolation etc resulting in better images suitable for diagnosis. The algorithmic computations in real-time may have high level of time based complexity and hence the use of digital signal processors (DSPs) for the implementation of such algorithms is proposed here. We employed TI 320 DM642 DSP for the purpose of image enhancement and edge detection purposes in our work. The problem required us to develop algorithms that are time and memory efficient and worked in agreement with real time specifications. This application desires that the DSPs be highly computationally efficient while working on low power. We thus discuss further the approach we followed while working on the above said platform and its applications in the field of medical research.
1. Introduction Real time medical imaging in todays world has become a field which requires ultra high speed processing. In order to satisfy this we have inculcated image processing algorithms on TI 320 DM642 DSP processor where the source of images has been considered from BOSCH camera and Sonline Adara Ultrasound Image system. Medical images enhancement and edge detection is an important work for object recognition of the human organs and it is an essential pre-processing requirement in medical imaging. The effect of the edge detection decides the result of the final processed image. Conventionally, edge is detected according to some early brought forward algorithms like Sobel algorithm, Canny algorithm and Laplacian of Gaussian operator(zero crossing method in our case) , but in theory they belong to