An algorithm for image processing is proposed. The proposed algorithm, which can be viewed as a quantum-classical hybrid algorithm, can transform a low-resolution bitonal image of a character from the set of alphanumeric characters (A-Z, 0-9) into a high-resolution image. The quantum part of the proposed algorithm fruitfully utilizes a variant of Grover's search algorithm, known as the fixed point search algorithm. Further, the quantum part of the algorithm is simulated using CQASM and the advantage of the algorithm is established through the complexity analysis. Additional analysis has also revealed that this scheme for optical character recognition (OCR) leads to high confidence value and generally works in a more efficient manner compared to the existing classical, quantum, and hybrid algorithms for a similar task.
翻译:提出了图像处理的算法。 拟议的算法可以被视为量子古典混合算法,可以将一个字符的低分辨率位元图像从一组字母数字字符(A-Z, 0-9)转换成高分辨率图像。 拟议的算法的量子部分卓有成效地利用了格罗弗搜索算法的变种,称为固定点搜索算法。 此外, 算法的量子部分是使用CQASM模拟的,而算法的优势是通过复杂分析确定的。 进一步的分析还表明,这一光学字符识别(OCR)方案能带来高可信度值,而且一般来说,与类似任务的现有古典、量和混合算法相比,其效率更高。