Image Segmentation and Text Extraction Techniques for Efficient Information Retrieval

Wydyanto, . and Ade, Putra and Maria, Ulfa (2025) Image Segmentation and Text Extraction Techniques for Efficient Information Retrieval. Journal of Data Science, 2025 (15). pp. 1-15. ISSN 2805-5160

	Text jods2025_15.pdf - Published Version Available under License Creative Commons Attribution. Download (275kB)
	Text 801 - Published Version Available under License Creative Commons Attribution. Download (38kB)

Abstract

Image segmentation and text extraction are important tasks in the field of computer vision and image processing. Image segmentation and text extraction involve identifying and separating objects or regions within an image, and helping visually impaired individuals access visual content. The ability to accurately extract text from scene images can have various applications and benefits. This can help automatically generate captions or descriptions for images, making them more accessible to individuals with visual impairments. This can help in tasks such as indexing and image search, where the extracted text can be used to improve the accuracy and relevance of search results. In addition, the extracted text can be used for sentiment analysis or other forms of text-based analysis, providing valuable insights into the content and context of the images. As the techniques discussed in the paper have the potential to help enhance the utility and usability of scene images in various applications and domains.

Item Type:	Article
Uncontrolled Keywords:	Image Segmentation, Text Extraction, OCR, Visual Accessibility, Scene Images, Information Retrieval
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science Q Science > QA Mathematics > QA76 Computer software Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4050 Electronic information resources Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4450 Databases
Depositing User:	Unnamed user with email masilah.mansor@newinti.edu.my
Date Deposited:	10 Dec 2025 01:53
Last Modified:	10 Dec 2025 01:53
URI:	http://eprints.intimal.edu.my/id/eprint/2249

Actions (login required)

View Item