Sharif Digital Repository

Persian (Farsi) script is totally cursive and each character is written in several different forms depending on its former and later characters in the word. These complexities make automatic handwriting recognition of Persian a very hard problem and there are few contributions trying to work it out. This paper presents a novel practical approach to online recognition of Persian handwriting which is based on representation of inputs and patterns with very simple visual features and comparison of these simple terms. This recognition approach is tested over a set of Persian words and the results have been quite acceptable when the possible words where unknown and they were almost all correct in... 

In recent years there has been a great effort to enhance the computer-aided diagnosis systems, since proven similar pathologies, in the past, plays an important role in diagnosis of the current cases, content based medical image retrieval has been emerged. In this work we have designed a decision making machine in which utilizes sparse representation technique to preserve semantic category relevance among the retrieved images and the query image, this machine comprises optimized wavelets (adapted using lifting scheme) to extract appropriate visual features in order to grasp visual content of the images, afterwards by using some classical methods, Raw data vectors become applicable for sparse... 

This paper proposes a damage assessment framework based on the visual features of a damaged reinforced concrete shear wall, such as crack pattern distribution, crushing areal density, aspect ratio, and the presence of the boundary condition. The study contains two parts including: identifying the performance level of the damaged walls (i.e., Immediate Occupancy, Life Safety, and Collapse Prevention) and estimating the residual strength and drift ratio of the walls. The research database contains 236 images of 72 reinforced concrete shear walls tested in the laboratory under the quasi-static cyclic loadings at various drift ratios between 0 and 4%. To identify the performance level of a... 

This study proposes predictive equations for estimating the peak-experienced drift ratio of unreinforced masonry walls based on the visual characteristic of the damages. In this regard, a comprehensive database comprised of 190 images associated with 30 unreinforced masonry walls at different drift ratios between 0.0 and 1.1 percent is collected, and the visual features of the progressive damages are extracted. Various image processing filters are implemented to the images to quantify the cracking length and crushing areas. The filters are capable of distinguishing different crack patterns, such as joint cracking and block cracking. In the following, four scenarios are introduced based on... 

Content-based image retrieval (CBIR) has been one of the most active areas of research. The retrieval principle of CBIR systems is based on visual features such as colour, texture and shape or the semantic meaning of the images. A CBIR system can be used to locate medical images in large databases. This paper presents a CBIR system for retrieving digital human brain magnetic resonance images (MRI) based on textural features and the support vector machine (SVM) learning method. This system can retrieve similar images from the database in two groups: normal and tumoural. This research uses the knowledge of the CBIR approach to the application of medical decision support and discrimination...