Depth image object recognition using moment invariants


Tham, Jie Sheng and Chen, Yong Shen and Ahmad Fauzi, Mohammad Faizal and Chang, Yoong Choon (2016) Depth image object recognition using moment invariants. In: 2016 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW). IEEE, pp. 1-2. ISBN 978-1-5090-2073-7

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Moment invariants have been widely used in various applications in image pattern recognition research field due to its invariant features of translation, scaling and rotation. In this paper, a computer vision based ambient assisted living technique for drinking activity assistance by using moment invariant to recognize the depth image object was developed. The extracted depth image objects dataset contains different type of mugs with different views. We employed the invariant features on the extracted depth image objects to recognize and classify the objects into different categories. Experimental result shows that higher accuracy can be achieve with the proposed technique compared to existing methods on depth image objects recognition.

Item Type: Book Section
Uncontrolled Keywords: Object recognition, Image recognition, Statistics, Feature extraction, Aging, Senior citizens
Subjects: T Technology > TA Engineering (General). Civil engineering (General) > TA1501-1820 Applied optics. Photonics
Divisions: Faculty of Engineering (FOE)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 14 Dec 2017 14:39
Last Modified: 14 Dec 2017 14:39


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