A Morphological Approach to Text String Extraction from Regular Periodic Overlapping Text/Background Images

A digitized image that consists of text strings and uniformly distributed background symbols must be segmented if the characters in the text string are to be recognized. This paper describes the development and implementation of a morphological approach to character string extraction from overlapping text/background images that minimizes the shape distortion of characters. The effectiveness of this algorithm is demonstrated on several test images.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/31369/3/0000281.pd

Détermination du niveau de brai dans une anode crue par analyse d’images

L’aluminium primaire est produit à partir de l’alumine (Al2O3) selon le procédé Hall-Héroult. Le procédé consiste à la réduction de l’alumine en aluminium par le carbone dans des cuves électrolytiques. L’anode de carbone représente donc un élément incontournable dans ce processus. Non seulement elle est source de carbone, mais elle joue le rôle de conducteur électrique. La qualité des anodes en carbone utilisées dans les cuves d’électrolyse représente ainsi l'un des paramètres les plus importants qui affectent la production de l'aluminium primaire. La pâte d’anode, qui est préparée en utilisant un mélange de coke de pétrole, de brai de houille et de matériaux recyclés, est compactée dans un vibro-compacteur pour former des anodes crues. Dans leur fabrication, le brai agit comme un liant. Sa bonne distribution aura forcément un impact positif sur leur qualité. Ces anodes sont cuites dans des fours de cuisson avant leur utilisation dans les cuves électrolytiques. La qualité de la matière première et les paramètres du processus de fabrication ont un impact significatif sur les caractéristiques de l’anode, notamment la composition chimique, la conductivité électrique, la résistance aux chocs thermiques, l’homogénéité et les réactivités à l’air et au dioxyde de carbone (CO2). Aussi, la qualité des anodes joue un rôle majeur dans la consommation d’énergie, le coût de production et les émissions de gaz à effet de serre. Les études développées pour déterminer le niveau de brai dans les anodes crues utilisent pour la plupart le microscope électronique à balayage ou le microscope optique. Ce qui donne de bons résultats au laboratoire sur de petits échantillons. Toutefois, ces méthodes ne sont pas pratiques sur les lignes de production qui exigent des résultats instantanés. Ainsi, la détection de la distribution du brai sur une surface d'anode est faite visuellement dans les usines. L’objectif de cette étude est de développer une méthode pour déterminer de façon instantanée la répartition du brai sur la face des anodes industrielles crues par l’analyse d’images. Pour ce faire, un logiciel d'analyse d'images a été mis au point et peut rapidement déterminer la répartition du brai sur la surface de l'anode. Le logiciel peut déterminer si la surface de l’anode est en sur-brai ou en sous-brai. Il permet aussi de déterminer la non-homogénéité de la répartition du brai. La mise en oeuvre de ce logiciel est basée sur le fait que toute couleur résulte de la combinaison des trois couleurs primaires que sont le rouge, le vert et le bleu (RGB). Ainsi, en se fixant des seuils pour ces différentes couleurs primaires, il est possible de trouver quelques critères pour identifier le haut niveau de brai. Par ailleurs, le niveau de brai influence l’état de surface des anodes. L’algorithme de Canny est utilisé pour déterminer les limites de particules, et le filtre de Gauss permet d’annuler les bruits générés par l’algorithme de Canny. Le logiciel d’analyse d’images développé est utilisé pour analyser les images d’anodes crues obtenues à l’aide d’un système de prise d’images. Ce système est constitué essentiellement d’un dispositif d'éclairage pour l'éclairage uniforme de surface de l'anode et d’une caméra numérique pour la capture des images. Pour mener à bien cette étude, il a été nécessaire de travailler à l'aluminerie et au laboratoire de l'UQAC pour collecter des données de niveau de brai des anodes crues dans des conditions d’opération différentes et de les analyser. Il s’agit aussi de colliger les résultats de ces différentes analyses d’images avec les caractéristiques des anodes. C’est dans ce sens que plusieurs anodes industrielles avec différentes spécificités ont été fabriquées pour être analysées. Par ailleurs, des anodes de laboratoire avec différentes spécifications couvrant le pourcentage de brai dans les recettes, la répartition granulométrique et différentes conditions de fabrication de l'anode crue ont été produites à l’UQAC. Une analyse chimique a permis de confirmer les résultats de l’analyse d’images. Il s’agit par ailleurs d’une analyse spectrophotométrique des échantillons prélevés dans les zones d’anodes industrielles et de laboratoire indiquées en sur-brai ou en sous-brai par le logiciel d’analyse d’images. Ces zones ont été préalablement sectionnées et moulinées. Les échantillons obtenus ont ensuite été immergés dans du solvant durant un temps bien déterminé pour dissoudre le brai avant l’analyse au spectrophotomètre. Certains résultats de l’analyse chimique de l’ensemble de ces anodes ont permis de parfaire le logiciel d’analyse d’images, et les résultats non utilisés de l’analyse chimique ont été comparés avec ceux de l’analyse d’images pour la validation du logiciel. Primary aluminum is produced from alumina (Al2O3) using the Hall-Heroult process. The method consists of reducing alumina to aluminum using carbon in electrolytic cells. The carbon anode represents an essential element in this process. It is a source of carbon as well as an electrical conductor. The quality of the carbon anodes used in the electrolytic cells is one of the most important parameters that affect the production of primary aluminum. The anode paste, which is prepared by using a mixture of petroleum coke, coal tar pitch, and recycled material, is compacted in a vibro-compactor to form green anodes. These anodes are baked in furnaces before being used in the electrolytic cells. The quality of the raw material and the parameters of the manufacturing process have a significant impact on the anode properties such as the chemical composition, electrical conductivity, thermal shock resistance, homogeneity, and air and CO2 reactivities. The anode quality plays a major role in energy consumption, production cost, and emissions of greenhouse gases. During their manufacture, the pitch acts as a binder. A good distribution of pitch has a positive impact on anode quality. Most of published studies show the use of the optical or scanning electron microscope to determine the pitch distribution. This works well in the laboratory for small samples. The objective of this study is to determine the distribution of pitch on the surface of industrial green anodes by image analysis. To do this, an image analysis software using the Canny algorithm and the distribution of primary colors red, green and blue (RGB) has been developed that can rapidly determine the distribution of pitch on the surface of the anode. This software can determine if the surface of the anode is over-pitched or under-pitched. It can determine the non-homogeneity of the distribution of pitch on the anode surface. In addition, the Gauss filter is used to cancel the noise generated by the Canny algorithm. The developed image analysis software is used to analyze the images of green anode surfaces obtained using an image capture system. This system contains essentially a light for the uniform illumination of the anode surface and a digital camera for capturing images. This study was carried out partly in an aluminum smelter and partly in the carbon laboratory of the UQAC/AAI Chair in order to collect information on the pitch level of green anodes fabricated under different operating conditions, and the results were analyzed. These results from the image analyses were correlated with the characteristics of the anodes. For this purpose, a number of anodes with different properties were produced at the plant. In addition, laboratory anodes with different specifications, including the percentage of pitch, the distribution of particle size, and different green anode manufacturing conditions, were produced in the carbon laboratory at UQAC. A method based on chemical analysis was used to validate the results of the image analysis software developed in the current study. This involved the spectrophotometric analysis of samples taken from different parts of industrial and laboratory anodes that were identified as over-pitch and under-pitch by the image analysis software. The samples were crushed and then were soaked in solvent for a certain time to dissolve pitch before the analysis in the spectrophotometer. Some results of the chemical analysis of lab and industrial anodes helped further improve the image analysis software, and the remaining chemical analysis results allowed the validation of the software by comparing them with those of the image analysis

Computer analysis of composite documents with non-uniform background.

The motivation behind most of the applications of off-line text recognition is to convert data from conventional media into electronic media. Such applications are bank cheques, security documents and form processing. In this dissertation a document analysis system is presented to transfer gray level composite documents with complex backgrounds and poor illumination into electronic format that is suitable for efficient storage, retrieval and interpretation. The preprocessing stage for the document analysis system requires the conversion of a paper-based document to a digital bit-map representation after optical scanning followed by techniques of thresholding, skew detection, page segmentation and Optical Character Recognition (OCR). The system as a whole operates in a pipeline fashion where each stage or process passes its output to the next stage. The success of each stage guarantees that the operation of the system as a whole with no failures that may reduce the character recognition rate. By designing this document analysis system a new local bi-level threshold selection technique was developed for gray level composite document images with non-uniform background. The algorithm uses statistical and textural feature measures to obtain a feature vector for each pixel from a window of size (2 n + 1) x (2n + 1), where n ≥ 1. These features provide a local understanding of pixels from their neighbourhoods making it easier to classify each pixel into its proper class. A Multi-Layer Perceptron Neural Network is then used to classify each pixel value in the image. The results of thresholding are then passed to the block segmentation stage. The block segmentation technique developed is a feature-based method that uses a Neural Network classifier to automatically segment and classify the image contents into text and halftone images. Finally, the text blocks are passed into a Character Recognition (CR) system to transfer characters into an editable text format and the recognition results were compared to those obtained from a commercial OCR. The OCR system implemented uses pixel distribution as features extracted from different zones of the characters. A correlation classifier is used to recognize the characters. For the application of cheque processing, this system was used to read the special numerals of the optical barcode found in bank cheques. The OCR system uses a fuzzy descriptive feature extraction method with a correlation classifier to recognize these special numerals, which identify the bank institute and provides personal information about the account holder. The new local thresholding scheme was tested on a variety of composite document images with complex backgrounds. The results were very good compared to the results from commercial OCR software. This proposed thresholding technique is not limited to a specific application. It can be used on a variety of document images with complex backgrounds and can be implemented in any document analysis system provided that sufficient training is performed.Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .A445. Source: Dissertation Abstracts International, Volume: 66-02, Section: B, page: 1061. Advisers: Maher Sid-Ahmed; Majid Ahmadi. Thesis (Ph.D.)--University of Windsor (Canada), 2004

Sugar crystal size characterization using digital image processing.

Thesis (PhD)-University of KwaZulu-Natal, Durban, 2007.The measurement of the crystal size distribution is a key prerequisite in optimising the growth of sugar crystals in crystalisation pans or for quality control of the final product. Traditionally, crystal size measurements are carried out by inspection or using mechanical sieves. Apart from being time consuming, these techniques can only provide limited quantitative information. For this reason, a more quantitative automatic system is required. In our project, software routines for the automated measurement of crystal size using classical image analysis techniques were developed. A digital imaging technique involves automatically analyzing a captured image of a representative sample of ~ 100 crystals for the automated measurement of crystal size has been developed. The main problem of crystals size measurements using image processing is the lack of an efficient algorithm to identify and separate overlapping and touching crystals which otherwise compromise the accuracy of size measurement. This problem of overlapping and touching crystals was addressed in two ways. First, 5 algorithms which identify and separate overlapping and touching crystals, using mathematical morphology as a tool, were evaluated. The accuracy of the algorithms depends on the technique used to mark every crystal in the image. Secondly, another algorithm which used convexity measures of the crystals based on area and perimeter, to identify and reject overlapping and touching crystals, have been developed. Finally, the two crystal sizing algorithms, the one applies ultimate erosion followed by a distance transformation and the second uses convexity measures to identify overlapping crystals, were compared with well established mechanical sieving technique. Using samples obtained from a sugar refinery, the parameters of interest, including mean aperture (MA) and coefficient of variance (CV), were calculated and compared with those obtained from the sieving method. The imaging technique is faster, more reliable than sieving and can be used to measure the full crystal size distributions of both massecuite and dry product