Texture analysis and discrimination in additive noise
Computer Vision, Graphics, and Image Processing
Use of gray value distribution of run lengths for texture analysis
Pattern Recognition Letters
Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image characterizations based on joint gray level-run length distributions
Pattern Recognition Letters
From image analysis to computer vision: an annotated bibliography, 1955-1979
Computer Vision and Image Understanding
Texture Classification by Wavelet Packet Signatures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Morphological Image Analysis: Principles and Applications
Morphological Image Analysis: Principles and Applications
Color Texture Classification by Normalized Color Space Representation
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
Efficient huge-scale feature selection with speciated genetic algorithm
Pattern Recognition Letters
A Branch and Bound Algorithm for Feature Subset Selection
IEEE Transactions on Computers
Automatic Image Segmentation by Tree Pruning
Journal of Mathematical Imaging and Vision
Computer Vision and Image Understanding
Evaluation of robustness and performance of early stopping rules with multi layer perceptrons
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
A histogram-based approach for object-based query-by-shape-and-color in image and video databases
Image and Vision Computing
Image-based quality monitoring system of limestone ore grades
Computers in Industry
Automatic watershed segmentation of randomly textured color images
IEEE Transactions on Image Processing
Histogram-based segmentation in a perceptually uniform color space
IEEE Transactions on Image Processing
Morphological grayscale reconstruction in image analysis: applications and efficient algorithms
IEEE Transactions on Image Processing
Texture analysis and classification with tree-structured wavelet transform
IEEE Transactions on Image Processing
Integrated feature architecture selection
IEEE Transactions on Neural Networks
Analysis of the back-propagation algorithm with momentum
IEEE Transactions on Neural Networks
Gradient descent learning algorithm overview: a general dynamical systems perspective
IEEE Transactions on Neural Networks
Genetic wavelet packets for speech recognition
Expert Systems with Applications: An International Journal
Genetic programming based blind image deconvolution for surveillancesystems
Engineering Applications of Artificial Intelligence
Engineering Applications of Artificial Intelligence
Beyond cross-domain learning: Multiple-domain nonnegative matrix factorization
Engineering Applications of Artificial Intelligence
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Measuring the quality parameters of materials at mines is difficult and a costly job. In this paper, an image analysis-based method is proposed efficiently and cost effectively that determines the quality parameters of material. The image features are extracted from the samples collected from a mine and modeled using neural networks against the actual grade values of the samples generated by chemical analysis. The dimensions of the image features are reduced by applying the genetic algorithm. The results showed that only 39 features out of 189 features are sufficient to model the quality parameter. The model was tested with the testing data set and the result revealed that the estimated grade values are in good agreement with the real grade values (R^2=0.77). The developed method was then applied to a case study mine of iron ore. The case study results show that proposed image-based algorithm can be a good alternative for estimating quality parameters of materials at a mine site. The effectiveness of the proposed method was verified by applying it on a limestone deposit and the results revealed that the method performed equally well for the limestone deposit.