Artificial Neural Network-based Approach for Plate Segmentation and Character Recognition

A procedure is presented for Plate Segmentation and Character Recognition through artificial neural network (ANN). All the tasks are accomplished using following steps. Violation Detection, Violation Plate localization, and Plate Recognition. The neural network was able to learn the nonlinear relationship between the pixel ratios for each of the nine blocks and a unique character and are able to help us out In resolving Artificial Neural Network-based Approach for Plate Segmentation and Character Recognition proble

A Neural Network-based Approach for the Machine Vision of Character Recognition

In this paper, an attempt is made to develop off-line recognition strategies for the isolated Handwritten English character(A to Z) and (0 to 9). Challenges in handwritten character recognition wholly lie in the variation and distortion of handwritten characters, since different people may use different style of handwritten, and direction to draw the same shape of the characters of their known script. The paper provides a review on the process of character recognition using neural network. Character recognition methods are listed under two main headlines. The Offline methods use the static images properties. The Offline methods are further divided into four methods, which are clustering, Feature Extraction, Pattern Matching and Artificial Neural Network. The Online methods are subdivided into k-NN classifier and direction based algorithm. Character preprocessing is used binarization, thresolding and segmentation method. Neural network based method improves the character recognition. The proposed method is based on the feed forward back propogation method to classify the characters. The ANN is trained using the Back Propogation algorithm. In the proposed system, English nue-merical letter is represented by binary numbers that are assume as input and fed to an ANN. Neural network followed by Back Propagation Algorithm which compromises Training

Global distribution and diversity of marine Verrucomicrobia

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Nature Publishing Group for personal use, not for redistribution. The definitive version was published in The ISME Journal 6 (2012): 1499-1505, doi:10.1038/ismej.2012.3.Verrucomicrobia is a bacterial phylum that is commonly detected in soil but little is known about the distribution and diversity of this phylum in the marine environment. To address this, we analyzed the marine microbial community composition in 506 samples from the International Census of Marine Microbes as well as eleven coastal samples taken from the California Current. These samples from both the water column and sediments covered a wide range of environmental conditions. Verrucomicrobia were present in 98% of the analyzed samples and thus appeared nearly ubiquitous in the ocean. Based on the occurrence of amplified 16S rRNA sequences, Verrucomicrobia constituted on average 2% of the water column and 1.4% of the sediment bacterial communities. The diversity of Verrucomicrobia displayed a biogeography at multiple taxonomic levels and thus, specific lineages appeared to have clear habitat preference. We found that Subdivision 1 and 4 generally dominated marine bacterial communities, whereas Subdivision 2 was confined to low salinity waters. Within the subdivisions, Verrucomicrobia community composition were significantly different in the water column compared to sediment as well as within the water column along gradients of salinity, temperature, nitrate, depth, and overall water column depth. Although we still know little about the ecophysiology of Verrucomicrobia lineages, the ubiquity of this phylum suggests that it may be important for the biogeochemical cycle of carbon in the ocean.We would like to thank the UCI Undergraduate Research Opportunity Program (S.F.), the National Science Foundation (OCE-0928544 and OCE-1046297, A.C.M.) and the Alfred P. Sloan Foundation (S.H., D.M.W., M.S.) for supporting the work