Classification of Handwritten Characters: Definition, Identification and Utilisation of Regional Characteristics for Lower Case English Characters

A new procedure for the classification of lower case English language characters is presented in this work . The character image is binarised and the binary image is further grouped into sixteen smaller areas ,called Cells . Each cell is assigned a name depending upon the contour present in the cell and occupancy of the image contour in the cell. A data reduction procedure called Filtering is adopted to eliminate undesirable redundant information for reducing complexity during further processing steps . The filtered data is fed into a primitive extractor where extraction of primitives is done . Syntactic methods are employed for the classification of the character . A decision tree is used for the interaction of the various components in the scheme . 1ike the primitive extraction and character recognition. A character is recognized by the primitive by primitive construction of its description . Openended inventories are used for including variants of the characters and also adding new members to the general class . Computer implementation of the proposal is discussed at the end using handwritten character samples . Results are analyzed and suggestions for future studies are made. The advantages of the proposal are discussed in detail .

Learning-Based Approach to Real Time Tracking and Analysis of Faces

This paper describes a trainable system capable of tracking faces and facialsfeatures like eyes and nostrils and estimating basic mouth features such as sdegrees of openness and smile in real time. In developing this system, we have addressed the twin issues of image representation and algorithms for learning. We have used the invariance properties of image representations based on Haar wavelets to robustly capture various facial features. Similarly, unlike previous approaches this system is entirely trained using examples and does not rely on a priori (hand-crafted) models of facial features based on optical flow or facial musculature. The system works in several stages that begin with face detection, followed by localization of facial features and estimation of mouth parameters. Each of these stages is formulated as a problem in supervised learning from examples. We apply the new and robust technique of support vector machines (SVM) for classification in the stage of skin segmentation, face detection and eye detection. Estimation of mouth parameters is modeled as a regression from a sparse subset of coefficients (basis functions) of an overcomplete dictionary of Haar wavelets.

De la ontología de la imagen-cine a la ética del primer plano

Este texto propone un análisis ontológico y ético de la imagen-cine como simulacro. Se consideran tres posturas diferentes: la platónica, la bergsoniana y la deleuziana. El cine de Ingmar Bergman utiliza los elementos de la nueva imagen-cine y resalta el primer plano por expresar el devenir subjetivo y las relaciones interpersonales.

A camera based digit location and recognition system for garment tracking

Garment information tracking is required for clean room garment management. In this paper, we present a camera-based robust system with implementation of Optical Character Reconition (OCR) techniques to fulfill garment label recognition. In the system, a camera is used for image capturing; an adaptive thresholding algorithm is employed to generate binary images; Connected Component Labelling (CCL) is then adopted for object detection in the binary image as a part of finding the ROI (Region of Interest); Artificial Neural Networks (ANNs) with the BP (Back Propagation) learning algorithm are used for digit recognition; and finally the system is verified by a system database. The system has been tested. The results show that it is capable of coping with variance of lighting, digit twisting, background complexity, and font orientations. The system performance with association to the digit recognition rate has met the design requirement. It has achieved real-time and error-free garment information tracking during the testing.

Generating segmented meshes from textured color images

This paper presents a new framework for generating triangular meshes from textured color images. The proposed framework combines a texture classification technique, called W-operator, with Imesh, a method originally conceived to generate simplicial meshes from gray scale images. An extension of W-operators to handle textured color images is proposed, which employs a combination of RGB and HSV channels and Sequential Floating Forward Search guided by mean conditional entropy criterion to extract features from the training data. The W-operator is built into the local error estimation used by Imesh to choose the mesh vertices. Furthermore, the W-operator also enables to assign a label to the triangles during the mesh construction, thus allowing to obtain a segmented mesh at the end of the process. The presented results show that the combination of W-operators with Imesh gives rise to a texture classification-based triangle mesh generation framework that outperforms pixel based methods. Crown Copyright (C) 2009 Published by Elsevier Inc. All rights reserved.

Road and Traffic Signs Recognition using Vector Machines

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility.This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

A Contour-based Separation of VerticallyAttached Traffic Signs

This report presents an algorithm for locating the cut points for and separatingvertically attached traffic signs in Sweden. This algorithm provides severaladvanced digital image processing features: binary image which representsvisual object and its complex rectangle background with number one and zerorespectively, improved cross correlation which shows the similarity of 2Dobjects and filters traffic sign candidates, simplified shape decompositionwhich smoothes contour of visual object iteratively in order to reduce whitenoises, flipping point detection which locates black noises candidates, chasmfilling algorithm which eliminates black noises, determines the final cut pointsand separates originally attached traffic signs into individual ones. At each step,the mediate results as well as the efficiency in practice would be presented toshow the advantages and disadvantages of the developed algorithm. Thisreport concentrates on contour-based recognition of Swedish traffic signs. Thegeneral shapes cover upward triangle, downward triangle, circle, rectangle andoctagon. At last, a demonstration program would be presented to show howthe algorithm works in real-time environment.

Hand Gesture Detection & Recognition System

The project introduces an application using computer vision for Hand gesture recognition. A camera records a live video stream, from which a snapshot is taken with the help of interface. The system is trained for each type of count hand gestures (one, two, three, four, and five) at least once. After that a test gesture is given to it and the system tries to recognize it.A research was carried out on a number of algorithms that could best differentiate a hand gesture. It was found that the diagonal sum algorithm gave the highest accuracy rate. In the preprocessing phase, a self-developed algorithm removes the background of each training gesture. After that the image is converted into a binary image and the sums of all diagonal elements of the picture are taken. This sum helps us in differentiating and classifying different hand gestures.Previous systems have used data gloves or markers for input in the system. I have no such constraints for using the system. The user can give hand gestures in view of the camera naturally. A completely robust hand gesture recognition system is still under heavy research and development; the implemented system serves as an extendible foundation for future work.

Instâncias da representação imagética hiper-real

The approach that undertakes this work revolves around the emergence of iconic structures on reflecting about the meaning of different methods of image representation through which the contemporaneity reveals itself. At baseline, three aspects are considered looking for an analytical ontology of the act of representation and imagery: the transition of representation in the oral culture of societies for writing, from these to typography, and finally the creation of a representation device. Resorted to, therefore, the argument by some genealogy reference points that technological instances such as writing, printing and photography, the evolution of this process, correspond, in itself, a consequent shift technique, for each representation precedent. In the area of the image, the most salient aspect of this change in foward process is the emergence of hyper-reality: the instances of hyper-realistic representation. In the Western context, the 'simulation of the world' - essential idea of mimesis is the work of an autonomous an conventional system. It should be noted, then the fact that under unreflective of the post-industrial societies, the mass-media image is coating with natural or fake code including - according to Baudrillard - tends to replace the real world in the "perpetuation of a large chain of simulacra." Hence in modern times, in the postindustrial society, during the crisis of the representation regimen and perception, centered in the referent. In this limit, new settings are established by aesthetic representations of imagery in contemporary culture: establishing spaces of simulation [Jean Baudrillard] the spectacle [Guy Debord] and hypermodernity [Gilles Lipovetsky] in which they operate. In these assemblages, saps the emergence of Hyper-reality Representation Instances - as seen in this study aesthetic events to configure itineraries of a new sensibility. It is the nature of this practice sign-iconic, ingrained in the creation of current artistic expression, which this research engaged in peering: the hyper-realistic setting, taking empirical support central to contemporary imagery production, diverse formats of analog representation.

Limiarização contextual automática de imagens coloridas: aplicação na extração de sementes de rodovia

In this paper is a totally automatic strategy proposed to reduce the complexity of patterns ( vegetation, building, soils etc.) that interact with the object 'road' in color images, thus reducing the difficulty of the automatic extraction of this object. The proposed methodology consists of three sequential steps. In the first step the punctual operator is applied for artificiality index computation known as NandA ( Natural and Artificial). The result is an image whose the intensity attribute is the NandA response. The second step consists in automatically thresholding the image obtained in the previous step, resulting in a binary image. This image usually allows the separation between artificial and natural objects. The third step consists in applying a preexisting road seed extraction methodology to the previous generated binary image. Several experiments carried out with real images made the verification of the potential of the proposed methodology possible. The comparison of the obtained result to others obtained by a similar methodology for road seed extraction from gray level images, showed that the main benefit was the drastic reduction of the computational effort.

Utilizando mapas de conectividade fuzzy no desenvolvimento de algoritmos reparadores de imagens binárias 3D

A 3D binary image is considered well-composed if, and only if, the union of the faces shared by the foreground and background voxels of the image is a surface in R3. Wellcomposed images have some desirable topological properties, which allow us to simplify and optimize algorithms that are widely used in computer graphics, computer vision and image processing. These advantages have fostered the development of algorithms to repair bi-dimensional (2D) and three-dimensional (3D) images that are not well-composed. These algorithms are known as repairing algorithms. In this dissertation, we propose two repairing algorithms, one randomized and one deterministic. Both algorithms are capable of making topological repairs in 3D binary images, producing well-composed images similar to the original images. The key idea behind both algorithms is to iteratively change the assigned color of some points in the input image from 0 (background)to 1 (foreground) until the image becomes well-composed. The points whose colors are changed by the algorithms are chosen according to their values in the fuzzy connectivity map resulting from the image segmentation process. The use of the fuzzy connectivity map ensures that a subset of points chosen by the algorithm at any given iteration is the one with the least affinity with the background among all possible choices

Unsupervised segmentation method for cuboidal cell nuclei in histological prostate images based on minimum cross entropy

This paper presents a novel segmentation method for cuboidal cell nuclei in images of prostate tissue stained with hematoxylin and eosin. The proposed method allows segmenting normal, hyperplastic and cancerous prostate images in three steps: pre-processing, segmentation of cuboidal cell nuclei and post-processing. The pre-processing step consists of applying contrast stretching to the red (R) channel to highlight the contrast of cuboidal cell nuclei. The aim of the second step is to apply global thresholding based on minimum cross entropy to generate a binary image with candidate regions for cuboidal cell nuclei. In the post-processing step, false positives are removed using the connected component method. The proposed segmentation method was applied to an image bank with 105 samples and measures of sensitivity, specificity and accuracy were compared with those provided by other segmentation approaches available in the specialized literature. The results are promising and demonstrate that the proposed method allows the segmentation of cuboidal cell nuclei with a mean accuracy of 97%. © 2013 Elsevier Ltd. All rights reserved.

Os deslimites da poesia e os reflexos do mundo: uma leitura de No banheiro um espelho trincado

Lyric poetry is where the relationships between world perception, language and representation are mostly problematized. In fact, poetic creation oscillates between the desire of a realistic expression of the world, beings and things and the understanding that its urgent task is simply to reinvent the world order and denaturalize it. Thus, Sérgio Mello’s poems in No Banheiro um Espelho Trincado (2004) conceive a poetry mainly concerned on the tension between words and things; between the lyric subject and the world; between language and the reality it encloses, through groups of images that range from the natural to the rupture process. His poems are small pieces of narrative, scenes that are articulated through the cutting technique, like the process of a cinematographic edition.

The Influence of Fractures on Vulnerability to Pollution of a Carbonate Aquifer: Monte Conero (Italy)

The carbonate outcrops of the anticline of Monte Conero (Italy) were studied in order to characterize the geometry of the fractures and to establish their influence on the petrophysical properties (hydraulic conductivity) and on the vulnerability to pollution. The outcrops form an analog for a fractured aquifer and belong to the Maiolica Fm. and the Scaglia Rossa Fm. The geometrical properties of fractures such as orientation, length, spacing and aperture were collected and statistically analyzed. Five types of mechanical fractures were observed: veins, joints, stylolites, breccias and faults. The types of fractures are arranged in different sets and geometric assemblages which form fracture networks. In addition, the fractures were analyzed at the microscale using thin sections. The fracture age-relationships resulted similar to those observed at the outcrop scale, indicating that at least three geological episodes have occurred in Monte Conero. A conceptual model for fault development was based on the observations of veins and stylolites. The fracture sets were modelled by the code FracSim3D to generate fracture network models. The permeability of a breccia zone was estimated at microscale by and point counting and binary image methods, whereas at the outcrop scale with Oda’s method. Microstructure analysis revealed that only faults and breccias are potential pathways for fluid flow since all veins observed are filled with calcite. According this, three scenarios were designed to asses the vulnerability to pollution of the analogue aquifer: the first scenario considers the Monte Conero without fractures, second scenario with all observed systematic fractures and the third scenario with open veins, joints and faults/breccias. The fractures influence the carbonate aquifer by increasing its porosity and hydraulic conductivity. The vulnerability to pollution depends also on the presence of karst zones, detric zones and the material of the vadose zone.

Differential block coding of bilevel images

Abstract- In this correspondence, a simple one-dimensional (1-D) differencing operation is applied to bilevel images prior to block coding to produce a sparse binary image that can be encoded efficiently using any of a number of well-known techniques. The difference image can be encoded more efficiently than the original bilevel image whenever the average run length of black pixels in the original image is greater than two. Compression is achieved because the correlation between adjacent pixels is reduced compared with the original image. The encoding/decoding operations are described and compression performance is presented for a set of standard bilevel images.