Text line segmentation method

a text line and segmentation technology, applied in the field of document image processing, can solve the problems of distorted input to the word/character recognition module, wrong output, and difficulty in obtaining a general algorithm that can work well on a variety of writing samples, and achieve the effect of robust way of identifying text lines

Active Publication Date: 2019-05-30
KONICA MINOLTA LAB U S A INC
View PDF0 Cites 8 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0006]The present invention is directed to an improved text line segmentation method for a ICR/IWR system, whi

Problems solved by technology

Many methods have been described, but it is difficult to obtain a general algorithm that can work well on a variety of writing samples having different slope, slant, inter-line connections, etc.
Errors in text line segmentation lead to distorte

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Text line segmentation method
  • Text line segmentation method
  • Text line segmentation method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0026]FIG. 1 schematically illustrates a conventional line segmentation method for handwritten documents, as described in Louloudis 2009. The method starts with an input text document image (S100), which is a binary image including foreground pixels (i.e. black pixels) representing text content and background pixels (e.g. white pixels). A connected component analysis is applied to the input image to extract connected components (step S101). A connected component (CC) is a group of connected foreground pixels. The properties of the CCs, such as their centroids, bounding boxes (a CC bounding box is a rectangular box with horizontal and vertical sides that bounds a CC), and heights are computed in this step. Then, the CCs are divided into three subsets based on their sizes, using an average height of the CCs as the average character height to set the criteria for division (step S102). The three subsets are referred to as a first subset for normal size, a second subset for large size, a...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

In a text line segmentation process, connected components (CCs) in document image are categorized into three subsets (normal, large, small) based on their sizes. The centroids of the normal size CCs are used to perform line detection using Hough transform. Among the detected candidate lines, those with line bounding box heights greater than a certain height are removed. For each normal size CC, if its bounding box does not overlap the bounting box of any line with an overlap area greater than a predefined fraction of the CC bounding box, a new line is added for this CC, which passes through the centroid of the CC and has an average slant angle. Each large size CCs are broken into two or more CCs. All CCs are then assigned to the nearest lines. A refinement method is also described, which can take any text line segmentation result and refine it.

Description

BACKGROUND OF THE INVENTIONField of the Invention[0001]This invention relates to document image processing, and in particular, it relates to a method for text line segmentation for document images.Description of Related Art[0002]Text line segmentation, i.e., segmenting lines of text from a document image (e.g. handwritten documents), is an important part of an intelligent character / word recognition (ICR / IWR) system. Many methods have been described, but it is difficult to obtain a general algorithm that can work well on a variety of writing samples having different slope, slant, inter-line connections, etc.[0003]In the field of offline intelligent word / character recognition, a conventional ICR / IWR system typically includes the following stages for processing an input text document image: text line segmentation; word / character segmentation; and a recognition module (usually CNN of kNN), to generate output word or character. Robust text line and word segmentation is a major bottleneck...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00G06K9/62G06K9/46G06T11/20G06V10/44G06V10/48
CPCG06K9/00463G06K9/6223G06K9/4633G06T11/20G06T2210/12G06V30/412G06V30/414G06V10/267G06V10/48G06V10/44G06V10/763G06F18/23213
Inventor AGARWAL, SHUBHAMZHANG, YONGMIAN
Owner KONICA MINOLTA LAB U S A INC
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap