The purpose of this paper color images with complex background for text and non-text segmentation is to propose a new system. The existing text extraction methods in the case of images with complex background do not work efficiently. Locating text in case of variation in style, color, as well as complex image background makes text reading from images challenging. Here the approach used is based...

We show that existing methods for training preposition error correction systems, whether using well-edited text or error-annotated corpora, do not generalize across very different test sets. We present a new, large errorannotated corpus and use it to train systems that generalize across three different test sets, each from a different domain and with different error characteristics. This new co...

This paper presents a parsing system for the detection of syntactic errors. It combines a robust partial parser which obtains the main sentence components and a finite-state parser used for the description of syntactic error patterns. The system has been tested on a corpus of real texts, containing both correct and incorrect sentences, with promising results.

In this paper we explore features for text detection within images of scenes containing other background objects using a Support Vector Machine (SVM) algorithm. In our approach, the Haar-like features are designed and utilised on banks of bandpass filters and phase congruency edge maps. The designed features with SVM leverages the properties of text geometry and colour for better differentiatio...

In this paper, we introduce a novel end-end framework for multi-oriented scene text detection from an instanceaware segmentation perspective. We present Fused Text Segmentation Networks, which combine multi-level features during feature extracting as text instance may rely on finer feature expression compared to general objects. It detects and segments the text instance jointly and simultaneous...

Text detection and recognition is a hot topic for researchers in the field of image processing. It gives attention to Content based Image Retrieval community in order to fill the semantic gap between low level and high level features. Several methods have been developed for text detection and extraction that achieve reasonable accuracy for natural scene text as well as multi-oriented text. Howe...

While the field of grammatical error detection has progressed over the past few years, one area of particular difficulty for both native and non-native learners of English, comma placement, has been largely ignored. We present a system for comma error correction in English that achieves an average of 89% precision and 25% recall on two corpora of unedited student essays. This system also achiev...

Polish Corpus of Suicide Notes (henceforth PCSN) is constructed to meet the needs of forensic linguistics. Suicide notes are messages created in borderline situation, shortly before death. Hence the annotation schema requires a complex description of a document structure, the textual content, as well as its linguistic properties. TEI was selected as the basis for the document encoding schema. T...

Annotating a corpus with error information is a challenging task. This paper describes the design, evaluation and refinement of an annotation scheme for Spanish article errors in learner data, so that future work on corpus annotation and automatic article error detection can progress. To evaluate reliability, 300 noun phrases with definite, indefinite and zero article have been tagged by four a...

The field of grammatical error correction (GEC) has grown substantially in recent years, with research directed at both evaluation metrics and improved system performance against those metrics. One unvisited assumption, however, is the reliance of GEC evaluation on error-coded corpora, which contain specific labeled corrections. We examine current practices and show that GEC’s reliance on such ...