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.
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Sood, A., Sharma, S. (2016). Image Segmentation and Object Recognition Using Machine Learning. In: Unal, A., Nayak, M., Mishra, D.K., Singh, D., Joshi, A. (eds) Smart Trends in Information Technology and Computer Communications. SmartCom 2016. Communications in Computer and Information Science, vol 628. Springer, Singapore. https://doi.org/10.1007/978-981-10-3433-6_25
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DOI: https://doi.org/10.1007/978-981-10-3433-6_25
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