Interrelationship identification between humans from images using two class classifier

Language Identification using Classifier Ensembles

In this paper we describe the language identification system we developed for the Discriminating Similar Languages (DSL) 2015 shared task. We constructed a classifier ensemble composed of several Support Vector Machine (SVM) base classifiers, each trained on a single feature type. Our feature types include character 1–6 grams and word unigrams and bigrams. Using this system we were able to outp...

Gabor Filter Based Multi-class Classifier for Scanned Document Images

When scanning documents with a large number of pages such as books, it is often feasible to provide a minimal number of training samples to personalize the system to compensate for global shifts in how the document was created or in scanning parameters. In this paper, we present a supervised multi-class classifier based on Gabor filters that is used to classify the scripts, font-faces, and font...

A class of binary images thinning using two PCNNs

This paper proposes a new algorithm for a class of binary images thinning by using two PCNNs (pulse coupled neural networks). Once the travelling pulses of the two PCNNs meet, the thinning result is obtained. The criterion of pulses meeting is given, and the parameters of the PCNNs are also specified, which make the implementation of the proposed thinning algorithm easier. The algorithm is used...

Segmentation of Fingerprint Images Using Linear Classifier

An algorithm for the segmentation of fingerprints and a criterion for evaluating the block feature are presented. The segmentation uses three block features: the block clusters degree, the blockmean information, and the block variance. An optimal linear classifier has been trained for the classification per block and the criteria of minimal number of misclassified samples are used. Morphology h...

Estimating Class Membership Probabilities using Classifier Learners