NDLI: A neural-net computing algorithm for detecting edges in a gray scale image

Content Provider	IEEE Xplore Digital Library
Author	Xue, K. Breznik, C.W.
Copyright Year	1990
Description	Author affiliation: Dept. of Electr. Eng., Wright State Univ., Dayton, OH, USA (Xue, K.; Breznik, C.W.)
Abstract	The algorithm presented features simple connections between neurons and is highly effective in detecting edges in noisy gray-scale images. The algorithm consists of two steps: image filtering and edge detection. The image filtering portion detects the zero crossings of D/sub i//sup 2/G (x, y) * l(x, y) where D/sub i//sup 2/G (x, y) represents the second derivative taken in the ith direction of a 2-9 Gaussian function. The output is then normalized and used to initialize the ith layer of a multiple-layer, Hopfield-type, neural network with simple localized connections. During edge detection, processing elements either excite (cooperate with) or inhibit (complete with) processing elements in other positions and layers. The competitive-cooperative process among the processing elements builds up edges and eliminates noise. The algorithm was simulated by using only four orientations: 0 degrees , 45 degrees , 90 degrees , and 135 degrees . Simulation results show the algorithm's performance on images with varying levels of noise. The output of this algorithm could be suitable input for a pattern recognition network.<>
Starting Page	2368
Ending Page	2373
File Size	664141
Page Count	6
File Format	PDF
DOI	10.1109/CDC.1990.204051
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-12-05
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Filters Humans Neural networks Filtering algorithms Computational modeling Machine vision Military computing Intelligent networks Neurons
Content Type	Text
Resource Type	Article

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