Automated Marble Plate Classification System Based On Different Neural Network Input Training Sets and PLC Implementation

by   Irina Topalova, et al.

The process of sorting marble plates according to their surface texture is an important task in the automated marble plate production. Nowadays some inspection systems in marble industry that automate the classification tasks are too expensive and are compatible only with specific technological equipment in the plant. In this paper a new approach to the design of an Automated Marble Plate Classification System (AMPCS),based on different neural network input training sets is proposed, aiming at high classification accuracy using simple processing and application of only standard devices. It is based on training a classification MLP neural network with three different input training sets: extracted texture histograms, Discrete Cosine and Wavelet Transform over the histograms. The algorithm is implemented in a PLC for real-time operation. The performance of the system is assessed with each one of the input training sets. The experimental test results regarding classification accuracy and quick operation are represented and discussed.



page 2

page 5


Performance Evaluation of Different Techniques for texture Classification

Texture is the term used to characterize the surface of a given object o...

Feasibility of Genetic Algorithm for Textile Defect Classification Using Neural Network

The global market for textile industry is highly competitive nowadays. Q...

Texture CNN for Thermoelectric Metal Pipe Image Classification

In this paper, the concept of representation learning based on deep neur...

A New Simple Vision Algorithm for Detecting the Enzymic Browning Defects in Golden Delicious Apples

In this work, a simple vision algorithm is designed and implemented to e...

Chi-Square Test Neural Network: A New Binary Classifier based on Backpropagation Neural Network

We introduce the chi-square test neural network: a single hidden layer b...

Automated Surface Texture Analysis via Discrete Cosine Transform and Discrete Wavelet Transform

Surface roughness and texture are critical to the functional performance...

Massive Enhanced Extracted Email Features Tailored for Cosine Distance

In this paper, the process of converting the Enron email dataset (the ve...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.