Multiple classifier fusion may generate more accurate classification than each of the constituent classifiers. Fusion is often based on fixed combination rules like the product and average. Only under strict probabilistic conditions can these rules be justified. We present here a simple rule for adapting the class combiner to the application. c decision templates (one per class) are estimated w...

One of the main applications of pattern recognition is the use of video or imaging cameras in order to detect and recognize the vehicle license plate numbers. This is important mainly for access, traffic surveillance and law enforcement. Several systems are implemented and working in situ with more or less precision. These systems are based on the use of a feature set extracted from the best vi...

Classifier fusion may generate more accurate classification than each of the basic classifiers. Fusion is often based on fixed combination rules like the product, average etc. This paper presents decision templates as classifier fusion method for the recognition of the handwritten English and Farsi numerals (1-9). The process involves extracting a feature vector on well-known image databases. T...

Handwritten recognition is a very active research domain that led to several works in the literature for the Latin Writing. The current systems tendency is oriented toward the classifiers combination and the integration of multiple information sources. In this paper, we describe two approaches for Arabic handwritten recognition using optimized Multiple classifier system MCS . The first rests on...

Different learning algorithms for the decision fusion mapping of a multiple classifier system are compared in this paper. It is very well known that the confusion matrices of the individual classifiers are utilised in the naive Bayes combination of classifier outputs. After a brief review of the decision templates, the linear associative memory and the pseudoinverse matrix approaches it is demo...

Hidden Markov models (HMMs) have been shown to provide a high level performance for detecting anomalies in sequences of system calls to the operating system kernel. Using Boolean conjunction and disjunction functions to combine the responses of multiple HMMs in the ROC space may significantly improve performance over a ‘‘single best’’ HMM. However, these techniques assume that the classifiers a...

Although the subject of fusion is well studied, the effects of normalisation prior to fusion are somewhat less well investigated. In this study, four normalisation techniques and six commonly used fusion classifiers were examined. Based on 24 (fusion classifiers) as a result of pairing the normalisation techniques and classifiers applied on 32 fusion data sets, 4×6×32 = 768 fusion experiments w...

06054. Abstract It is proposed an approach to solution of image recognition problems based on the following principal thesises: a) images are represented by multiple partial models widely used in pattern recognition – feature sets; b) algorithms are multiple classifiers: each algorithm use its own data – some partial image model; c) there are two kinds of fusion – data (partial models) fusion a...

combining classifiers appears as a natural step forward when a critical mass of knowledge of single classifier models has been accumulated. Although there are many unanswered questions about matching classifiers to real-life problems, combining classifiers is rapidly growing and enjoying a lot of attention from pattern recognition and machine learning communities. For any pattern classification...

In this paper, we propose a special fusion method for combining ensembles of base classifiers utilizing new neural networks in order to improve overall efficiency of classification. While ensembles are designed such that each classifier is trained independently while the decision fusion is performed as a final procedure, in this method, we would be interested in making the fusion process more a...