Object detection in images using morphlet descriptions
Y.V. Vizilter, V.S. Gorbatsevich, S.V. Sidyakin, B.V. Vishnyakov

 

State Research Institute of Aviation Systems (GosNIIAS), Moscow, Russia

Full text of article: Russian language.

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Abstract:
An original method for object detection based on morphlet trees is proposed in the paper. It allows the robust detection of heterogeneous objects in images to be done without pre-training. Besides, the detection process simultaneously includes a preliminary segmentation, which can be later used for recognition. Also, there is another important characteristic: the proposed approach does not require the use of sliding windows and feature pyramids to detect different-scale objects.

Keywords:
mathematical morphology, Pytiev morphology, object detection, morphlets.

Citation:
Vizilter YV, Gorbatsevich VS,Vishnyakov BV, Sidyakin SV. Object detection in images using morphlet descriptions, Computer Optics 2017; 41(3): 406-411. DOI: 10.18287/2412-6179-2017-41-3-406-411.

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