Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a novel scheme for representing character string images in the scanned document.  converted conventional multi-dimensional descriptors into pseudo-codes which have a property that: if two vectors are near in the original space then encoded pseudo-codes are 'semi equivalent with high probability. For this conversion,  combined locality sensitive hashing (LSH) indices and at the same time  also developed a new family of LSH functions that is superior to earlier ones when all vectors are constrained to lie on the surface of the unit sphere. Word spotting based on our pseudo-code becomes faster than multi-dimensional descriptor-based method while it scarcely degrades the accuracy.
['Kengo Terasawa', 'Yuzuru Tanaka']
I am writing a research paper on a idea Locality Sensitive Pseudo-Code for Document Images
[{"from": "human", "value": "I am writing a research paper on a idea Locality Sensitive Pseudo-Code for Document Images"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  propose a novel scheme for representing character string images in the scanned document.  converted conventional multi-dimensional descriptors into pseudo-codes which have a property that: if two vectors are near in the original space then encoded pseudo-codes are 'semi equivalent with high probability. For this conversion,  combined locality sensitive hashing (LSH) indices and at the same time  also developed a new family of LSH functions that is superior to earlier ones when all vectors are constrained to lie on the surface of the unit sphere. Word spotting based on our pseudo-code becomes faster than multi-dimensional descriptor-based method while it scarcely degrades the accuracy."}]