The morphological operators of a hit-miss transformation, opening, and closing are generalized in a number of ways. The new operators are useful for solving a variety of binary image analysis problems that involve pattern detection and reconstruction. Generalized openings are developed by replacing erosions with hit-miss operators. These new openings are shown to be anti-extensive, idempotent, ...

A new system approach for image understanding, the image consulting framework, is proposed. It allows for the validation of image properties. Kinds of image properties considered are textual, textural, hierarchically, color and symbolically. Its main application field is information filtering from images used in world wide web documents. The image consulting framework consists of four stages, t...

In this paper, we present a novel methodology on document image analysis (DIA) which harnesses the mechanism of preattentive visual guidance in human vision. Summarizing the psychophysical research on preattentive vision, we suggest using two types of computations to simulate this biological process: the visual similarity clustering and visual saliency detection. Based on the computational impl...

A new bottom-up method is described that clusters the content of a mixed type document into text or non-text areas. The proposed approach is based on a new set of features combined with a self-organized neural network classifier. The set of features corresponds to the contents and the relationship of 3 3 3 masks, is selected by using a statistical reduction procedure, and provides texture infor...

Title of Dissertation: Your Dissertation Title Your Full Name, Doctor of Philosophy, 1997 Dissertation directed by: Academic title and name of advisor Department of Mathematics Image compression usually considers the minimization of storage space as its main objective. It is desirable, however, to code images so that we have the ability to process the resulting representation directly. In this ...

Collinear arrangement of objects (such as, text elements or continuous lines) is integral part of any office document image, whether structured or unstructured. The ability to analyze such an organization of objects thus provides the basic and important building block for a plethora of image analysis applications. Most Hough Transform-based line detection approaches do not furnish line widths a...

PixED (from Pixel to Electronic Document) is aimed at converting document images into structured electronic documents which can be read by a machine for information retrieval. The approach is based on the combination of perception and symbol reading which are the two processes involved when humans detect the organisation of a document. "Pre-attentive reading" denotes the physical segmentation r...

In this chapter, we discuss the use of Self Organizing Maps (SOM) to deal with various tasks in Document Image Analysis. The SOM is a particular type of artificial neural network that computes, during the learning, an unsupervised clustering of the input data arranging the cluster centers in a lattice. After an overview of the previous applications of unsupervised learning in document image ana...

Document Image Understanding (DIU) is an interesting research area with a large variety of challenging applications. Researchers have worked from decades on this topic, as witnessed by the scientific literature. The main purpose of the present report is to describe the current status of DIU with particular attention to two subprocesses: document skew angle estimation and page decomposition. Sev...

Text block segmentation is necessary in document layout analysis. An algorithm and its implementation that segregates text block by block (a block is either a title or a paragraph) from the provided document, e.g. newspaper image, based on pyramid structure is described in this paper. The pyramid structure, which is amenable for parallel processing on output, is a multi-resolution image represe...