BOOK-CHAPTER

Image Segmentation and Object Recognition Using Machine Learning

Ashima SoodSahil Sharma

Year: 2016 Communications in computer and information science Pages: 204-210   Publisher: Springer Science+Business Media

Abstract

The digital image processing is a fast pace growing field which requires pre-processing of the images before their actual usage and experimentation. Image Segmentation and Object Recognition is one of the phase which requires the prior information about the object to give the extracted attributes as output of the images. Here, in the present research work we have already some outdoor segmented images which have been identified as to which category of classification they belong. This work has been accelerated with the help of machine learning that is a novel technique to identify the objects with outstanding accuracy. The machine learning algorithms have aided in this process of identifying the objects like sky, brick, cement, grass etc. This collaboration of image segmentation with machine learning has proved to be accessible in large datasets where after segmentation images can classify themselves into a category provided it has attributes of the images.

Keywords:
Computer science Artificial intelligence Segmentation Object (grammar) Process (computing) Computer vision Image segmentation Field (mathematics) Image processing Pace Pattern recognition (psychology) Digital image Cognitive neuroscience of visual object recognition Machine learning Image (mathematics) Mathematics Geography

Metrics

4
Cited By
0.27
FWCI (Field Weighted Citation Impact)
13
Refs
0.69
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology

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