Conference Proceedings
APCOM XXV
Conference Proceedings
APCOM XXV
The Application of Nueral Networks to Size Analysis of Material on Conveyors
The underlying theory behind the construction of an on-line size analysis
system is described together with an introduction to the Artificial
Intelligent techniques that it is founded on. Previous systems based on
more traditional technology such as edge detection and dilation
algorithms have been restricted by the significant processing power they
require, this has resulted in the production of systems with either reduced
functionality or severe hardware requirements. A neural network approach offered a new perspective to the problem of
size analysis; the ability of a network to learn and recognise subtle
patterns in training data before on-line processing is initiated opened up
the possibility for the production of a fully functioning practical system.
The format of the training data had to be carefully analysed prior to its
implementation in a neural network as the capability of a neural network
solution depends as much upon a suitable data preparation as it does on
the system architecture. To facilitate experimentation with various profile quantification
techniques such as fourier and fractal analysis an Image Profile Analysis
System was constructed (IPAS) in software on a personal computer. The
IPAS system was produced with the aim of pre-processing image data to
create data sets for experimenting with external neural network packages.
The system allows the analysis of both real images obtained by image
capture and simulated images created by an in-built in simulator. A
measurement comparison scheme is also included together with a case
study concerned with the frequency analysis of simulated images. The power of neural networks combined with the data compression
provided by profiling removes the need for direct measurement of
individual particles. This has obvious implications on the level of
hardware necessary, and ultimately the expense of a stand alone system.
The extrusive nature of data collection via an image analysis system will
also permit simple installation of a shipped system; eliminating any
requirement for interference with existing machinery.
system is described together with an introduction to the Artificial
Intelligent techniques that it is founded on. Previous systems based on
more traditional technology such as edge detection and dilation
algorithms have been restricted by the significant processing power they
require, this has resulted in the production of systems with either reduced
functionality or severe hardware requirements. A neural network approach offered a new perspective to the problem of
size analysis; the ability of a network to learn and recognise subtle
patterns in training data before on-line processing is initiated opened up
the possibility for the production of a fully functioning practical system.
The format of the training data had to be carefully analysed prior to its
implementation in a neural network as the capability of a neural network
solution depends as much upon a suitable data preparation as it does on
the system architecture. To facilitate experimentation with various profile quantification
techniques such as fourier and fractal analysis an Image Profile Analysis
System was constructed (IPAS) in software on a personal computer. The
IPAS system was produced with the aim of pre-processing image data to
create data sets for experimenting with external neural network packages.
The system allows the analysis of both real images obtained by image
capture and simulated images created by an in-built in simulator. A
measurement comparison scheme is also included together with a case
study concerned with the frequency analysis of simulated images. The power of neural networks combined with the data compression
provided by profiling removes the need for direct measurement of
individual particles. This has obvious implications on the level of
hardware necessary, and ultimately the expense of a stand alone system.
The extrusive nature of data collection via an image analysis system will
also permit simple installation of a shipped system; eliminating any
requirement for interference with existing machinery.
Contributor(s):
Maxwell A P, Denby B, Miles N J
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- Published: 1995
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