forest classification on the basis of satellite images is a promising technique both for primary map production and for map updating and forest monitoring. for accurate for-est classification into three classes, using mapping by canopy cover density “high spatial resolution satellite images have to be used in order to obtain the required spatial detail” [schneider, 1999]. at the same time, the ...

Almost all document analysis approaches need to perform a global analysis of the page orientation as a separate process at an early stage. It would be preferable to estimate the orientation locally after page segmentation and classification, when more knowledge about the different regions is available. In this paper, a novel local skew estimation method is presented that takes advantage of the ...

land cover classification is one of the most important applications of polarimetric radar images, especially in urban areas. there are numerous features that can be extracted from these images for the use of their high potential, hence feature selection plays an important role in polsar image classification. in this study, three main steps are used to improve the classification: 1) feature extr...

In this paper, a high-speed document image classification algorithm is presented. The algorithm is based on the bottom-up strategy which can successfully segment and classify any type of sophisticated layout documents without the limitation of Manhattan rules. Special techniques are employed to overcome the slow speed problem facing most of the bottomup algorithms. During segmentation process, ...

In this paper we consider the problem of separating noisy instantaneous linear mixtures of document images in the Bayesian framework. The source image is modeled hierarchically by a latent labeling process representing the common classifications of document objects among different color channels and the intensity process of pixels given the class labels. A Potts Markov random field is used to m...

The main contribution of this paper is a new method for classifying document images by combining textual and visual features repectively extracted with the Bag of Words (BoW) and the Bag of Visual Words (BoVW) techniques. While previous attempts have been showing disappointing results by combining visual and textual features with the Borda-count technique, we’re proposing here a combination thr...

Automatic Pattern Recognition field has witnessed enormous growth in the past few decades. Being an essential element of Pattern Recognition, Document Image Analysis is the procedure of analyzing a document image with the intention of working out the contents so that they can be manipulated as per the requirements at various levels. It involves various procedures like document classification, o...