# A quantum segmentation algorithm based on local adaptive threshold for NEQR image

arXiv: https://arxiv.org/abs/2311.11953 · HTML: https://mlsanity.com/paper/2311.11953/

## Key facts

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- First posted on arXiv 2 Oct 2023.

## Abstract (arXiv)

The classical image segmentation algorithm based on local adaptive threshold can effectively segment images with uneven illumination, but with the increase of the image data, the real-time problem gradually emerges. In this paper, a quantum segmentation algorithm based on local adaptive threshold for NEQR image is proposed, which can use quantum mechanism to simultaneously compute local thresholds for all pixels in a gray-scale image and quickly segment the image into a binary image. In addition, several quantum circuit units, including median calculation, quantum binarization, etc. are designed in detail, and then a complete quantum circuit is designed to segment NEQR images by using fewer qubits and quantum gates. For a 2n× 2n image with q gray-scale levels, the complexity of our algorithm can be reduced to O(n2+q), which is an exponential speedup compared to the classic counterparts. Finally, the experiment is conducted on IBM Q to show the feasibility of our algorithm in the noisy intermediate-scale quantum (NISQ) era.