Learning-based license plate detection using global and local features

This paper proposes a license plate detection algorithm using both global statistical features and local Haar-like features. Classifiers using global statistical features are constructed firstly through simple learning procedures. Using these classifiers, more than 70% of background area can be excluded from further training or detecting. Then the AdaBoost learning algorithm is used to build up the other classifiers based on selected local Haar-like features. Combining the classifiers using the global features and the local features, we obtain a cascade classifier. The classifiers based on global features decrease the complexity of the system. They are followed by the classifiers based on local Haar-like features, which makes the final classifier invariant to the brightness, color, size and position of license plates. The encouraging detection rate is achieved in the experiments. © 2006 IEEE

The extraction of characters on dated color postcards

[[abstract]]A novel scheme is proposed to extract characters from dated postcards. The illustrations of the postcards appear in various languages and colors embedded in different backgrounds. Due to reproduction and uneven illumination, these characters suffer a severe degradation and hence extracting characters using conventional methods becomes difficult. A morphological operation is proposed to remove irrelevant backgrounds that are connecting to border edges of the postcards. As a result, characters become the most obvious objects. Followed by horizontal and vertical projections, the exact locations of the characters can be located. The proposed scheme has been executed on a set of color images of postcards and proved its efficacy[[conferencetype]]國際[[conferencedate]]20040627~20040630[[booktype]]紙本[[conferencelocation]]Taipei, Taiwa

A fast algorithm for license plate detection in various conditions

This paper proposes a fast algorithm detecting license plates in various conditions. There are three main contributions in this paper. The first contribution is that we define a new vertical edge map, with which the license plate detection algorithm is extremely fast. The second contribution is that we construct a cascade classifier which is composed of two kinds of classifiers. The classifiers based on statistical features decrease the complexity of the system. They are followed by the classifiers based on Haar-features, which make it possible to detect license plate in various conditions. Our algorithm is robust to the variance of the illumination, view angle, the position, size and color of the license plates when working in complex environment. The third contribution is that we experimentally analyze the relations of the scaling factor with detection rate and processing time. On the basis of the analysis, we select the optimal scaling factor in our algorithm. In the experiments, both high detection rate (with low false positive rate) and high speed are achieved when the algorithm is used to detect license plates in various complex conditions. © 2006 IEEE

Identification of Technical Journals by Image Processing Techniques

The emphasis of this study is put on developing an automatic approach to identifying a given unknown technical journal from its cover page. Since journal cover pages contain a great deal of information, determining the title of an unknown journal using optical character recognition techniques seems difficult. Comparing the layout structures of text blocks on the journal cover pages is an effective method for distinguishing one journal from the other. In order to achieve efficient layout-structure comparison, a left-to-right hidden Markov model (HMM) is used to represent the layout structure of text blocks for each kind of journal. Accordingly, title determination of an input unknown journal can be effectively achieved by comparing the layout structure of the unknown journal to each HMM in the database. Besides, from the layout structure of the best matched HMM, we can locate the text block of the issue date, which will be recognized by OCR techniques for accomplishing an automatic journal registration system. Experimental results show the feasibility of the proposed approach

Use of colour for hand-filled form analysis and recognition

Colour information in form analysis is currently under utilised. As technology has advanced and computing costs have reduced, the processing of forms in colour has now become practicable. This paper describes a novel colour-based approach to the extraction of filled data from colour form images. Images are first quantised to reduce the colour complexity and data is extracted by examining the colour characteristics of the images. The improved performance of the proposed method has been verified by comparing the processing time, recognition rate, extraction precision and recall rate to that of an equivalent black and white system

Localisation automatique de champs de saisie sur des images de formulaires couleur par isomorphisme de sous-graphe

International audienceThis paper presents an approach for spotting textual fields in colored forms. We proceed by locating these fields thanks to their neighboring context which is modeled with a structural representation. First, informative zones are extracted. Second, forms are represented by graphs in which nodes represent colored rectangles while edges represent neighboring links. Finally, the context of the queried region of interest is modeled as a graph. Subgraph isomorphism is applied in order to locate this ROI in the structural representation of a whole document. Evaluated on a 130-document image dataset, experimental results show up that our approach is efficient and that the requested information is found even if its position is changed.Cet article présente une approche permettant la localisation de champs de saisie sur des images couleur de formulaires. Ces champs sont localisés grâce à une modélisation structurelle représentant leur contexte. Dans un premier temps, les zones informatives sont ex-traites. Les formulaires sont ensuite représentés par des graphes au sein desquels les noeuds représentent des rectangles de couleur uniforme tandis que les arcs modélisent les relations de voisinage. Finalement, le voisinage de la région d'intérêt à localiser est également représenté par un graphe. Une recherche d'isomorphisme de sous graphe vise à localiser le graphe modélisant le voisinage de la région d'intérêt au sein de la représentation structurelle du document cible. Une expérimentation est réalisée sur une base de 130 images de document. Les résultats montrent l'efficacité de la méthode même si la position de la région d'intérêt est variable

Document image processing using irregular pyramid structure

Ph.DDOCTOR OF PHILOSOPH