Digital Signal Processing

1403 Submissions

[4] viXra:1403.0955 [pdf] submitted on 2014-03-28 09:21:32

Subject Recommendation Using Ontology for Computer Science ACM Curricula

Authors: A. A. Salama
Comments: 7 Pages.

Recommender systems are needed to find subject items of one’s interest. We review recommender systems and recommendation methods. We propose a subject personalization framework based on adaptive hypermedia for Computer Science ACM Curricula. We extend Hermes framework with subject recommendation functionality. We combine TF-IDF term extraction method with cosine similarity measure. Specialization and standard subject database are incorporated into the knowledgebase. Based on the performed evaluation, we conclude that semantic recommender systems in general outperform traditional recommenders systems with respect to accuracy, precision, and recall, and that the proposed recommender has a better F-measure than existing semantic recommenders.
Category: Digital Signal Processing

[3] viXra:1403.0580 [pdf] submitted on 2014-03-22 02:07:30

Direct Processing of Run-Length Compressed Document Image for Segmentation and Characterization of a Specified Block

Authors: Mohammed Javed, P. Nagabhushan, B.B. Chaudhuri
Comments: 6 Pages. Direct processing of compressed data, compressed document, TIFF Document Processing

Extracting a block of interest referred to as segmenting a specified block in an image and studying its characteristics is of general research interest, and could be a challenging if such a segmentation task has to be carried out directly in a compressed image. This is the objective of the present research work. The proposal is to evolve a method which would segment and extract a specified block, and carry out its characterization without decompressing a compressed image, for two major reasons that most of the image archives contain images in compressed format and 'decompressing' an image indents additional computing time and space. Specifically in this research work, the proposal is to work on run-length compressed document images.
Category: Digital Signal Processing

[2] viXra:1403.0577 [pdf] submitted on 2014-03-22 02:09:43

Automatic Detection of Font Size Straight from Run Length Compressed Text Documents

Authors: Mohammed Javed, P. Nagabhushan, B.B. Chaudhuri
Comments: 8 Pages. Automatic font size detection, compressed document processing, compressed domain

Automatic detection of font size finds many applications in the area of intelligent OCRing and document image analysis, which has been traditionally practiced over uncompressed documents, although in real life the documents exist in compressed form for efficient storage and transmission. It would be novel and intelligent if the task of font size detection could be carried out directly from the compressed data of these documents without decompressing, which would result in saving of considerable amount of processing time and space. Therefore, in this paper we present a novel idea of learning and detecting font size directly from run-length compressed text documents at line level using simple line height features, which paves the way for intelligent OCRing and document analysis directly from compressed documents. In the proposed model, the given mixed-case text documents of different font size are segmented into compressed text lines and the features extracted such as line height and ascender height are used to capture the pattern of font size in the form of a regression line, using which the automatic detection of font size is done during the recognition stage. The method is experimented with a dataset of 50 compressed documents consisting of 780 text lines of single font size and 375 text lines of mixed font size resulting in an overall accuracy of 99.67%.
Category: Digital Signal Processing

[1] viXra:1403.0061 [pdf] submitted on 2014-03-09 10:53:12

Computer Arithmetic of Geometrical Figures. Algorithms and Hardware Design. // Компьютерная арифметика геометрических фигур. Алгоритмы и аппаратура.

Authors: Solomon I. Khmelnik
Comments: 164 Pages. Book.

This book describes various versions of processors, designed for affine transformations of many-dimensional figures – planar and spatial. This processors is oriented to affine transformation of unstructured geometrical figures with arbitrary points distribution. The type of data presentation used in this book is non-conventional, based on a not well-known theory of vectors and geometrical figures coding. The problems of affine transformation are used widely in science and engineering. The examples of their application are computer tomography and data compression for telecommunication systems. The book covers the figures coding theory – the codes structure, algorithms of coding and decoding for planar and spatial figures, arithmetical operations with planar and spatial figures. The theory is supplemented by numerous examples. The arrangement of several versions of geometrical processor is considered – data representation, operating blocks, hardwares realization of coding, decoding and arithmetic operations algorithms. The processor’s internal performance is appraised. The book is designed for students, engineers and developers, who intend to use the computer arithmetic of geometrical figures in their own research and development in the field of specialized processors. // В книге рассматриваются различные варианты процессоров, предназначенных для аффинных преобразований многомерных фигур - плоских и пространственных. Эти процессоры ориентированы на аффинное преобразование неструктурированных геометрических фигур с произвольным характером распределения точек. При этом ипользуется нетрадиционная форма представления данных, основанная на малоизвестной теории кодирования векторов и геометрических фигур. Задачи аффинного преобразования пространства широко используются в науке и технике. В книге описывается теория кодирования фигур – структура кодов, алгоритмы кодирования, декодирования плоских и пространственных фигур, арифметические операции с плоскими и пространственными фигурами. Теория дополняется многочисленными примерами. Рассматривается несколько вариантов геометрического процессора – представление данных, операционные блоки, техническая реализация алгоритмов кодирования, декодирования и арифметических операций. Оценивается быстродействие этих процессоров.
Category: Digital Signal Processing