Ancient manuscripts have been preserved by many organizations so as to protect these documents and retrieve traditional knowledge. With the advanced computer technology, digitized media is now commonly used to record these documents. One objective of such work is to develop an efficient image processing system that could be used to retrieve knowledge and information automatically from these anc...

Business card images are of multiple natures as these often contain graphics, pictures and texts of various fonts and sizes both in background and foreground. So, the conventional binarization techniques designed for document images can not be directly applied on mobile devices. In this paper, we have presented a fast binarization technique for camera captured business card images. A card image...

This paper presents a textline detection method for degraded historical documents. Our method follows a conventional two-step procedure that the binarization is first performed and then the textlines are extracted from the binary image. In order to address the challenges in historical documents such as document degradation, structure noise, and skews, we develop new methods for the binarization...

In most OMR algorithms, the pre-processing stage consists on a binarization operation followed by the estimation of the staffline thickness and the vertical line distance within the same staff. Subsequent operation can use these values as references. This work presents an improvement on previous conventional estimates for the two reference lengths and consequently a novel binarization method ba...

The transition method for image binarization is based on the concept of t-transition pixels, a generalization of edge pixels, and t-transition sets. We introduce a novel unsupervised thresholding for unimodal histograms to estimate the transition sets. We also present dilation and incidence transition operators to refine the transition set. Afterward, we propose the simple edge transition opera...

This paper presents the results of a new approach for binarization of text images. The new technique uses the fuzzy C-means clustering algorithm to simulate the clustering performed by the human visual system. The clustering process was applied to eleven text images. All of them have black text but the background change in color. As a mean of comparison, binarization using the image histogram w...

In this paper the binarization of matrix codes is investigated as an application of supervised learning of image processing tasks using a recurrent version of the Neural Abstraction Pyramid. The desired network output is computed using an adaptive thresholding method for undegraded images. The network is trained to iteratively produce the same output even when the contrast is lowered and typica...

In this paper, we propose a novel methodology for text detection in indoor/outdoor scene images. The proposed methodology is based on an efficient binarization and enhancement technique followed by a suitable connected component analysis procedure. Image binarization successfully process indoor/ outdoor scene images having shadows, non-uniform illumination, low contrast and large signal-depende...

The increase in use of automated fingerprint recognition puts on it a challenge of processing a diverse range of fingerprints. To make it supportive in consisting fingerprint detail extraction, quality control is required, which is used in identification/verification. Fingerprint verification is one of the most reliable personal identification methods and it plays a very important role in foren...

The planned OCR formula to retrieve the text within the scanned document pictures. Here the text detection formula supported two machine learning classifiers: one permits generating candidate word regions and therefore the different filters out non-text ones. The extract connected elements (CCs) in pictures by victimization the maximally stable extremal region formula. In CC cluster adaboost cl...