The research of image segmentation methods for interested area extraction in image matching guidance

Yaozong Zhang; Pan Chen; Hanyu Hong; Zhenghua Huang; Chen Zhou

doi:10.1117/12.2539129

14 February 2020 The research of image segmentation methods for interested area extraction in image matching guidance

Yaozong Zhang, Pan Chen, Hanyu Hong, Zhenghua Huang, Chen Zhou

Proceedings Volume 11429, MIPPR 2019: Automatic Target Recognition and Navigation; 114290R (2020) https://doi.org/10.1117/12.2539129
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

The extraction of Region of Interest (ROI) is an important information guarantee in the application of imaging matching guidance, which directly affects the acquisition probability and matching accuracy of the target. Image segmentation is an important method to extract the Region of Interest of the target. Based on image segmentation algorithm, histogram equalization and morphological filtering, this paper proposes an effective image processing method to extract the Region of Interest of the target. (1) A variety of image threshold segmentation methods are applied to the actual processing flow, and their segmentation performance is compared and analyzed. Some image segmentation methods are obtained, which are suitable for target region extraction in template image preparation and target potential region location in matching recognition. (2) Preliminary localization of visible remote sensing images is carried, using color information, to obtain local regions, then enhance the image using histogram equalization method, finally morphological filtering is used to remove the edge noise. (3) The Otsu method and Kittler minimum error method are processed in parallel, then the segmentation results are fused, and the evaluation indexes such as area constraint, similarity and contrast are filtered to obtain the target region .Tests have been done with visible image and infrared image in this paper. The result indicates that the effectiveness of the morphological filter is more obvious after histogram equalization for the original image. Besides, the Otsu method and Kittler minimum error method are processed in parallel, then the segmentation results are fused to get a more precise Region of Interest, thus ensuring the accuracy and timeliness of imaging matching guidance.

Citation Download Citation

Yaozong Zhang, Pan Chen, Hanyu Hong, Zhenghua Huang, and Chen Zhou "The research of image segmentation methods for interested area extraction in image matching guidance", Proc. SPIE 11429, MIPPR 2019: Automatic Target Recognition and Navigation, 114290R (14 February 2020); https://doi.org/10.1117/12.2539129

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