CD-ROM document database standard

Phillips, Ihsin T.; Chen, S.; Haralick, Robert M.

doi:10.1109/icdar.1993.395691

Cited by 78 publications

(28 citation statements)

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“…A oneinch square patch of image data was extracted from the upper left corner of one zone classified as ''body text'' in each of 800 images on UW CDROM 1 3 . The other 179 images on the CDROM did not contain a zone classified as body text that was at least one-inch square.…”

Section: Resultsmentioning

confidence: 99%

<title>Document matching on CCITT Group 4 compressed images</title>

Hull

1997

SPIE Proceedings

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A method is proposed for detecting whether two CCITT group 4 images were scanned from the same document. Features are extracted from rectangular patches of text and compared with a modified Hausdorff distance measure. Two images are said to be ''equivalent'' (i.e., they were scanned from the same document) if the Hausdorff measure finds that a specified number of features are located within a given distance of one another in both images. This paper explains the technique and presents experimental results that demonstrate its effectiveness. It is shown that features extracted from a one-inch square patch of image data provide better than 95% correct retrieval accuracy with no false positives on a database of 800 documents.

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Section: Resultsmentioning

confidence: 99%

<title>Document matching on CCITT Group 4 compressed images</title>

Hull

1997

SPIE Proceedings

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“…The proposed algorithm works well for small skew angles (less than 10 degrees). Although skew detection methods without such restrictions are reported in the literature [14,4],in reality the skew seldom exceeds ±5 degrees [15]. Further work will be done in order to obtain better measure of the skew detection success.…”

Section: Discussionmentioning

confidence: 99%

Skew Detection based on Bounding Edge Approximation

Malathi¹

2014

IOSRJCE

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“…RSL formalizes decision making and captures operation sequences that transform interpretations represented as attributed graphs. One of the authors selected five challenging tables from the UW-I technical document corpus [15], and then produced a single set of table cells for each table. Both player algorithms return single interpretations.…”

Section: Example: a Table Cell Detection Gamementioning

confidence: 99%

Recognition Tasks Are Imitation Games

Zanibbi¹,

Blostein

Cordy

2005

Pattern Recognition and Data Mining

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Abstract. There is need for more formal specification of recognition tasks. Currently, it is common to use labeled training samples to illustrate the task to be performed. The mathematical theory of games may provide more formal and complete definitions for recognition tasks. We present an imitation game that describes a wide variety of recognition tasks, including the classification of isolated patterns and structural analysis. In each round of the game, a set of 'players' try to match the interpretation of an input produced by a set of 'experts.' The 'playing field' on which experts and players operate is a set of interpretations generated from legal sequences of 'moves' for a round. The expert and player moves transform interpretations, and select interpretations for output. The distance between interpretations in the playing field is defined by a distance metric for interpretations, and the game outcome by a ranking function on distance values observed for players' interpretations. We demonstrate how this imitation game may be used to define and compare recognition tasks, and clarify the evaluation of proposed solutions.

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CD-ROM document database standard

Cited by 78 publications

References 1 publication

<title>Document matching on CCITT Group 4 compressed images</title>

<title>Document matching on CCITT Group 4 compressed images</title>

Skew Detection based on Bounding Edge Approximation

Recognition Tasks Are Imitation Games

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