Unsupervised ensemble of experts (EoE) framework for automatic binarization of document images

In recent years, a large number of binarization methods have been developed, with varying performance generalization and strength against different benchmarks. In this work, to leverage on these methods, an ensemble of experts (EoE) framework is introduced, to efficiently combine the outputs of various methods. The proposed framework offers a new selection process of the binarization methods, which are actually the experts in the ensemble, by introducing three concepts: confidentness, endorsement and schools of experts. The framework, which is highly objective, is built based on two general principles: (i) consolidation of saturated opinions and (ii) identification of schools of experts. After building the endorsement graph of the ensemble for an input document image based on the confidentness of the experts, the saturated opinions are consolidated, and then the schools of experts are identified by thresholding the consolidated endorsement graph. A variation of the framework, in which no selection is made, is also introduced that combines the outputs of all experts using endorsement-dependent weights. The EoE framework is evaluated on the set of participating methods in the H-DIBCO'12 contest and also on an ensemble generated from various instances of grid-based Sauvola method with promising performance.Comment: 6-page version, Accepted to be presented in ICDAR'1

Native and non-native speakers of English in summarising expository texts

This study examines how native and non-native English speakers summarise expository texts. It investigates if there is any difference in quality between the summaries produced by two groups of students; namely native speakers of English, who acquire the language in early childhood and have their education (from kindergarten / grade 1 to high school) in English, and non-native speakers, who acquire the language in an ESL/EFL context. The sample consisted of seventy undergraduates from a private Malaysian university, comprising thirty-five native and thirty-five non-native speakers of English. Data for the study include summaries by students, response to teacher and student questionnaires as well as interviews with both teachers and students. The results of the study revealed that there was a significant difference in the quality of summaries of native and non-native English speakers in expository text