Development of android apps for image processing
With rapid development of mobile technology and image processing, mobile application involving image processing has been largely emerged in many fields. Android, a mobile operating system based on Linux kernel, has the largest installed base of all general-purpose operating systems. Now there are...
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sg-ntu-dr.10356-686782023-07-04T15:04:15Z Development of android apps for image processing Chen, Qian Tan Eng Leong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering With rapid development of mobile technology and image processing, mobile application involving image processing has been largely emerged in many fields. Android, a mobile operating system based on Linux kernel, has the largest installed base of all general-purpose operating systems. Now there are over one billion active Android users and the marketing of Android applications is still increasing. This report analyzes and compares the conventional image segmentation methods which all suffer from inaccuracy problems. It also proposes an effective interactive image segmentation algorithm based on color space. It mainly executes in two steps, firstly user is required to enclose a small sample region in the predefined region of interest. Then the programme will identify all the similar-color objects present in the image and label the connected components. Based on the selected component, the programme will recognize and classify the image into a specific category and display the meaning. The algorithm is implemented in MATLAB first and transferred to the Android application. The proposed method has significantly improved the segmentation and recognition accuracy. Both of the experiments can achieve an excellent and improved result. This programme can be applied in both entertainment and education. It has the recreation significance for people to process their images or photos as well as the education significance for students to understand the meaning of an image or an object. Master of Science (Communications Engineering) 2016-05-30T08:41:46Z 2016-05-30T08:41:46Z 2016 Thesis http://hdl.handle.net/10356/68678 en 90 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Chen, Qian Development of android apps for image processing |
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With rapid development of mobile technology and image processing, mobile
application involving image processing has been largely emerged in many fields.
Android, a mobile operating system based on Linux kernel, has the largest installed
base of all general-purpose operating systems. Now there are over one billion active
Android users and the marketing of Android applications is still increasing.
This report analyzes and compares the conventional image segmentation methods
which all suffer from inaccuracy problems. It also proposes an effective interactive
image segmentation algorithm based on color space. It mainly executes in two steps,
firstly user is required to enclose a small sample region in the predefined region of
interest. Then the programme will identify all the similar-color objects present in the
image and label the connected components. Based on the selected component, the
programme will recognize and classify the image into a specific category and display
the meaning. The algorithm is implemented in MATLAB first and transferred to the
Android application. The proposed method has significantly improved the
segmentation and recognition accuracy. Both of the experiments can achieve an
excellent and improved result.
This programme can be applied in both entertainment and education. It has the
recreation significance for people to process their images or photos as well as the
education significance for students to understand the meaning of an image or an
object. |
author2 |
Tan Eng Leong |
author_facet |
Tan Eng Leong Chen, Qian |
format |
Theses and Dissertations |
author |
Chen, Qian |
author_sort |
Chen, Qian |
title |
Development of android apps for image processing |
title_short |
Development of android apps for image processing |
title_full |
Development of android apps for image processing |
title_fullStr |
Development of android apps for image processing |
title_full_unstemmed |
Development of android apps for image processing |
title_sort |
development of android apps for image processing |
publishDate |
2016 |
url |
http://hdl.handle.net/10356/68678 |
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1772828524248301568 |