Text Detection in Natural Image By Connected Component Labeling

Authors

  • zamen abood ramadhan Computer Scince Department Mustansiriyah Univesity
  • Dhia Alzubaydi Computer Scince Department Mustansiriyah Univesity

DOI:

https://doi.org/10.23851/mjs.v30i1.531

Keywords:

Gaussian blur, edge detection, Canny edge detection, connected component, SWT.

Abstract

The process of detect the text from the natural image is complex and difficult process because the variance by the devises that take the images and different the texts that found in images in the orientation, size and style. Given the importance the texts in images in the several of application of computer vision. In this paper dependent on the spatial natural images and on the spatial data set for the street sign that include the texts by the different size and different orientation. In this paper detected the texts in images by using robust method by using several algorithms, at the first stage making preprocessing for the image to blur the image and reduce the nose on it by Gaussian blur, second stage making processing that include canny edge detection to detect the edges and dilation, third stage applying connected component to filling all objects in image then applying stroke width transform(SWT) to detect the letter candidate and applying the system on the several images that include different types of texts.

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References

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Key Dates

Published

15-08-2019

Issue

Section

Original Article

How to Cite

[1]
zamen abood ramadhan and D. Alzubaydi, “Text Detection in Natural Image By Connected Component Labeling”, Al-Mustansiriyah J. Sci., vol. 30, no. 1, pp. 111–118, Aug. 2019, doi: 10.23851/mjs.v30i1.531.

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