Earticle

초록

영어

This paper deals with one of the new emerging multimedia data types, namely, handwritten cursive text. The paper presents two indexing methods for searching a collection of cursive handwriting. The first index, called word-level index, treats word as pictogram and uses global features for representing the cursive words and their retrieval. Each word (or stroke)can be described with a set of features and, thus, can be stored as points in the feature space. The Karhunen-Loѐ. ve transform is then used to minimize the number of features used (data dimensionality) and thus the index size. Feature vectors are stored in an R-tree. The second index, called stroke-level index, treats the word as a set of strokes. We implemented both indexes and carried many simulation experiments to measure the effectiveness and the cost of the search algorithm. The proposed indexes achieve substantial saving in the search time over the sequential search. Moreover, the proposed indexes improve the matching rate up to 46% over the sequential search. The word-level index is suitable for large collection of cursive text. The stroke-level index is more accurate than the word-level index, but the stroke-level index is more costly than the word-level index in terms of the search time.

목차

Abstract
 1. Introduction
 2. Background
  2.1. R-trees
  2.2. Sequential Search in Handwritten Database
 3. The Proposed Word-level Index
  3.1. The Size of the Hyper-rectangle
  3.2. Global Features
 4. The proposed stroke-level index
  4.1. The basic idea
  4.2. Similarity search queries
  4.3. Feature space dimensionality
  4.4. Reducing the candidate set size
 5. Prior work
 6. Experimental results
  6.1. Evaluation of the global features
  6.2. Comparison between theComparison between the proposed Index and the Sequential Scan
 7. Conclusions
 References

저자

• Ibrahim Kamel [ Dept. of Electrical and Computer Engineering ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605