Abstract
Detection of edge is most basic operations which is needed in processing of objects in image processing identification. Hence, edge detection is the most likely operation for the processing of image in real-time applications with optimized results which is accurate, and architecture with less complexity results in less latency. Hence, edge detection with adaptive threshold technique plays a vital role in present-day edge detection techniques. The computation is carried with threshold values which are automatically adopted according to the image specification which helps to reduce the memory and computations along with decision-making will take less time. Hence, delay gets reduced with improved detection performance along with increased efficiency. The proposed architecture is implemented using Xilinx system generator tool on Spartan6 ATLYS board.
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Ojashwini, R.N., Gangadhar Reddy, R., Rani, R.N., Pruthvija, B. (2021). Edge Detection Canny Algorithm Using Adaptive Threshold Technique. In: Satapathy, S., Zhang, YD., Bhateja, V., Majhi, R. (eds) Intelligent Data Engineering and Analytics. Advances in Intelligent Systems and Computing, vol 1177. Springer, Singapore. https://doi.org/10.1007/978-981-15-5679-1_45
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DOI: https://doi.org/10.1007/978-981-15-5679-1_45
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