<p>In this paper, a graph based handwritten Tifinagh character recognition system is presented. In preprocessing Zhang Suen algorithm is enhanced. In features extraction, a novel key point extraction algorithm is presented. Images are then represented by adjacency matrices defining graphs where nodes represent feature points extracted by a novel algorithm. These graphs are classified using a graph matching method. Experimental results are obtained using two databases to test the effectiveness. The system shows good results in terms of recognition rate.</p>

In this paper we present method of features extraction based on decomposition of the characters into several simple geometric shapes (segment, arc)

Digital images of the retina is widely used for screening of patients suffering from sight threatening diseases such as Diabetic retinopathy and Glaucoma. The localization of the Optic Disc (OD) center is the first and necessary step identification and segmentation of anatomical structures and in pathological retinal images. From the center of the optic disc spreads the major blood vessels of the retina. Therefore, by considering the high number of vessels and the high number of the angles resulted from the vessels crossing, the authors propose a new method based on the number of angles in the vicinity of optic disc for localization of the center of optic disc. The first step is pre-processing of retinal image for separate the fundus from its background and increase the contrast between contours. In the second step, the authors use the Curvature Scale Space (CSS) for angle detection. In the next step, they move a window about the size of optic disc to count the number of corners. In the final step, they use the center of windows which has the most number of corners for localizing the optic disc center. The proposed method is evaluated on DRIVE, CHASE_DB1 and STARE databases and the success rate is 100, 100 and 96.3%, respectively.

Recognition of documents has become a basic necessity for two reasons: first to secure the existing data in paper because of the limited of their lives duration and the high rate of destruction insects, fire or humidity secondly to reduce space of archives. The aim of this work is to realize a converter that detects images and text within a document image taken by a scanner and applying a system for the recognition of characters (OCR) in order to obtain a web page (HTML extension) ready to be used in the same computer or on the web hosts to be accessible by everyone.

The document image converter is a necessity in our life for many reasons such as digitization of data in paper to secure them and gain time by automating this task, on the other hand preserving the environment by maintaining trees the first source of paper, for that this works based in a bi-cubic method for physical structure analyze and a graphs models representation for the characters recognition to generate at the end a standard XML file that can be used to create file is realised ( doc, pdf ,html…).