LINE SEGMENTATION METHOD APPLICABLE TO DOCUMENT IMAGES CONTAINING HANDWRITING AND PRINTED TEXT CHARACTERS OR SKEWED TEXT LINES

Patent №

US 9,104,940

Granted

2015-08-11

Filed 2013

Owner

KONICA MINOLTA LABORATORY U.S.A., INC.

Lab

AI components

3

nlp · vision · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

14015048

A text line segmentation method for a document image containing printed text and handwriting, or document image containing skewed lines or printed text. Connected component (CC) are obtained for the document, and their bounding boxes and centroids are calculated. The CCs are categorized into three categories based on bounding box sizes: small objects, regular text objects, and large objects involving handwriting. The centroids of regular text objects are used in a cluster analysis to find the vertical centers of the N text lines. Then, each CC is classified into one of the N lines based on the vertical distance between its centroid and the vertical centers of text lines, and copied into to a corresponding object board. Extra spaces are removed from the object boards to obtain the line segments. The large object involving handwriting will be classified into one of the lines but absent from other lines.

Natural languageVisionAI hardwareG06V 30/1478G06V 30/15G06V 30/153G06V 30/10

AI classification

Vision1.00
Natural language0.82
AI hardware0.53
Knowledge representation0.06
Planning0.00
Evolutionary computation0.00
Machine learning0.00
Speech0.00

Ownership

KONICA MINOLTA LABORATORY U.S.A., INC.

assignment · 311210426

Assignors

WU, CHAOHONG

On an employer assignment, the assignors are typically the inventors.

© 2026 NYSGPT2525 LLC