Title: Intelligent recognition method of colour multidimensional image boundary feature based on improved neural network

Authors: Jie Ding; Guotao Zhao; Huibing Hao; Chunping Li

Addresses: College of Technology, Hubei Engineering University, Xiaogan, 432000, China ' Hubei Engineering University, Xiaogan, 432000, China ' Hubei Engineering University, Xiaogan, 432000, China ' Hubei Engineering University, Xiaogan, 432000, China

Abstract: In order to improve the intelligent edge feature recognition ability of super-pixel colour multidimensional images, an improved neural network-based edge feature recognition algorithm for colour multidimensional images is proposed. A colour multi-dimensional image imaging model based on super-pixel fusion is constructed, and the edge contour of the multi-dimensional colour image is detected by using the colour block region fusion and segmentation method. The improved neural network adaptive optimisation method is used to segment and match the blocks of multi-dimensional colour images, and to extract the colour boundary information features of the multi-dimensional colour images. According to the RGB value of colour multi-dimensional image and neighbourhood mean, the adaptive fusion segmentation of colour multi-dimensional image is realised. The simulation results show that this method can effectively realise the intelligent recognition of super-pixel colour multi-dimensional image information boundary, the recognition accuracy is higher, and the ability of image recognition and target detection is improved.

Keywords: improved neural network; image; segmentation; detection; edge feature extraction.

DOI: 10.1504/IJICA.2019.102118

International Journal of Innovative Computing and Applications, 2019 Vol.10 No.2, pp.115 - 121

Received: 31 Jan 2019
Accepted: 30 Apr 2019
Published online: 06 Sep 2019 *

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