Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications that includes, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. Neural Network (NN) with its inherent learning ability offers promising solutions for handwritten characte...

The paper presents an application of rough sets and statistical methods to feature reduction and pattern recognition. The presented description of rough sets theory emphasizes the role of rough sets reducts in feature selection and data reduction in pattern recognition. The overview of methods of feature selection emphasizes feature selection criteria, including rough set-based methods. The pap...

In this paper, a learning-based paradigm for scientific chart recognition is proposed. Two kinds of chart recognition methods are presented: hidden Markov model based and neural network based method. A newly developed feature extraction method is also put forward for chart images. Experiments on three kinds of charts show that the ergodic hidden Markov models achieve a satisfactory result for c...

KEYWORDS Control chart pattern (CCP) recognition techniques are widely used to identify the potential process problems. Recently, artificial neural network (ANN)–based techniques are popular for this problem. However, finding the suitable architecture of an ANN-based CCP recognizer and its training process are time consuming and the obtained results are not interpretable. To facilitate the rese...

Control chart patterns (CCPs) can be associated with certain assignable causes, and recognition of such patterns can assist the diagnostic search for those causes. Variations could be one or more instances of trend, cyclic, hugging, sudden shift or some other variations over time. Each pattern has special statistical characteristics which differentiate one pattern from another. In a time series...

This paper presents a supervised competitive learning network approach, called a fuzzy-soft learning vector quantization, for control chart pattern recognition. Unnatural patterns in control charts mean that there are some unnatural causes for variations in statistical process control (SPC). Hence, control chart pattern recognition becomes more important in SPC. In order to detect e€ ectively t...