Smart Information Storage Platform with Intelligent Image Text Recognition Model

How to effectively analyze images and text, and how to efficiently compute and store them, is an issue that is in urgent need of research. In this research work, a novel smart information storage platform with the intelligent image text recognition model is studied. For the traditional models, they usually encounter many challenges, such as the image size is inaccurate, the probability of recognition is low, and the storage efficiency is too low. To deal with this, the proposed model has three novelties: (1) novel image recognition algorithm with small size of labeling is proposed. (2) novel efficient text recognition model is designed. (3) efficient image storage algorithm is proposed to ensure the performance of the intelligent platform. To evaluate the performance, the peak signal-to-noise ratio is calculated by the quality of the image after degradation, and the visual error of the original image and the degraded image are compared. The relationship between the dictionary level and the three variables of dictionary and hash table in the 3-byte hash value calculation method can be calculated to show the storage performance. After enough simulations, the PSNR reaches 17 on average, and the performance is proved to be efficient.