This paper aims to improve the feature extraction of Persian handwritten number recognition systems. In this paper, we introduced nine new features for detection and recognition of Persian handwritten digits using the technique of finding the smallest enclosing disc in computational geometry. All these features are based on the geometry form of numbers and are much better than the features in t...

The cursive nature of Persian alphabet, and the complex and convoluted rules regarding this script cause major challenges to segmentation as well as recognition of Persian words. We propose a new segmentation algorithm for the main stroke of online Persian handwritten words. Using this segmentation, we present a perturbation method which is used to generate artificial samples from handwritten w...

In this paper, extracted word features have been used toward offline detection of Persian handwritten words. This has been done using fourteen features in Persian word structure. In this method after required pre-processing, numbers and location of dots versus base line are extracted then the word becomes thin and the feature extraction stage starts. In this stage the words are detected by usin...

A new method for recognition of isolated handwritten Arabic/Persian digits is presented. This method is based on Support Vector Machines (SVMs), and a new approach of feature extraction. Each digit is considered from four different views, and from each view 16 features are extracted and combined to obtain 64 features. Using these features, multiple SVM classifiers are trained to separate differ...

In pursuit of Persian handwritten digit recognition, many machine learning techniques have been utilized. Mixture of experts (MOE) is one of the most popular and interesting combining methods which has great potential to improve performance in machine learning. In MOE, during a competitive learning process, the gating networks supervise dividing input space between experts and experts obtain sp...

handwritten digit recognition can be categorized as a classification problem. probabilistic neural network (pnn) is one of the most effective and useful classifiers, which works based on bayesian rule. in this paper, in order to recognize persian (farsi) handwritten digit recognition, a combination of intelligent clustering method and pnn has been utilized. hoda database, which includes 80000 p...

classification ensemble, which uses the weighed polling of outputs, is the art of combining a set of basic classifiers for generating high-performance, robust and more stable results. this study aims to improve the results of identifying the persian handwritten letters using error correcting output coding (ecoc) ensemble method. furthermore, the feature selection is used to reduce the costs of ...

The Persian language is one of the dominant languages in the Middle East, so there are significant amount of Persian documents available on the Web. Due to the special and different nature of the Persian language compared to other languages like English, the design of information retrieval systems in Persian requires special considerations. However, there are relatively few studies on retrieval...