抄録
Academic institutions such as universities and technical colleges usually employ paper-based examinations and reports to evaluate the academic performance of students. Consequently, teachers expend considerable time and energy in the marking of such paper-based examinations. We are developing an automatic paper marking system geared towards reducing this paper-marking burden on teachers. To execute paper marking, handwritten character lines are extracted from examination papers, and then characters on those lines are recognized. In this paper, we primarily discuss how the character line is extracted from handwritten examination papers without ruled lines. The extraction of character lines from non-ruled papers is difficult because of the writing characteristic of students. Further, extraction accuracy is an important factor in character recognition performance. Conventional character line extraction algorithms for printed documents perform poorly on this problem. Furthermore, most proposed methods conduct tests using document images that include only character lines. In this paper we develop a less time-consuming algorithm for this task.
| 元の言語 | English |
|---|---|
| ページ（範囲） | 481-488 |
| ページ数 | 8 |
| ジャーナル | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| 巻 | 9164 |
| DOI | |
| 出版物ステータス | Published - 2015 |
| 外部発表 | Yes |
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ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
これを引用
Speedy character line detection algorithm using image block-based histogram analysis. / Premachandra, Chinthaka; Goto, Katsunari; Tsuruoka, Shinji; Kawanaka, Hiroharu; Takase, Haruhiko.
：: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 巻 9164, 2015, p. 481-488.研究成果: Article
}
TY - JOUR
T1 - Speedy character line detection algorithm using image block-based histogram analysis
AU - Premachandra, Chinthaka
AU - Goto, Katsunari
AU - Tsuruoka, Shinji
AU - Kawanaka, Hiroharu
AU - Takase, Haruhiko
PY - 2015
Y1 - 2015
N2 - Academic institutions such as universities and technical colleges usually employ paper-based examinations and reports to evaluate the academic performance of students. Consequently, teachers expend considerable time and energy in the marking of such paper-based examinations. We are developing an automatic paper marking system geared towards reducing this paper-marking burden on teachers. To execute paper marking, handwritten character lines are extracted from examination papers, and then characters on those lines are recognized. In this paper, we primarily discuss how the character line is extracted from handwritten examination papers without ruled lines. The extraction of character lines from non-ruled papers is difficult because of the writing characteristic of students. Further, extraction accuracy is an important factor in character recognition performance. Conventional character line extraction algorithms for printed documents perform poorly on this problem. Furthermore, most proposed methods conduct tests using document images that include only character lines. In this paper we develop a less time-consuming algorithm for this task.
AB - Academic institutions such as universities and technical colleges usually employ paper-based examinations and reports to evaluate the academic performance of students. Consequently, teachers expend considerable time and energy in the marking of such paper-based examinations. We are developing an automatic paper marking system geared towards reducing this paper-marking burden on teachers. To execute paper marking, handwritten character lines are extracted from examination papers, and then characters on those lines are recognized. In this paper, we primarily discuss how the character line is extracted from handwritten examination papers without ruled lines. The extraction of character lines from non-ruled papers is difficult because of the writing characteristic of students. Further, extraction accuracy is an important factor in character recognition performance. Conventional character line extraction algorithms for printed documents perform poorly on this problem. Furthermore, most proposed methods conduct tests using document images that include only character lines. In this paper we develop a less time-consuming algorithm for this task.
KW - Character line
KW - Document image analysis
KW - Examination paper
KW - Figure detection
UR - http://www.scopus.com/inward/record.url?scp=84984645271&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84984645271&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-20801-5_53
DO - 10.1007/978-3-319-20801-5_53
M3 - Article
AN - SCOPUS:84984645271
VL - 9164
SP - 481
EP - 488
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
SN - 0302-9743
ER -