Robust Scraping Image Sequence Restoration Device

Abstract

The invention provides a robust scraping type image sequence restoring device which comprises an image sensor collection array timing control module, an image sensor collection array, a histogram threshold counting module, a digital quantitative module, an image correlation calculation module, an image change detection module, a sensor physical-parameter adjustment module, an RAM read-write control module and an RAM array. According to the robust scraping type image sequence restoring device, image collection objects with different properties can obtain frame images with high contrast uniformity, can collect the images and calculate information needed by image reconstruction at the same time. The function requirements of a general processor or a DSP (Digital Signal Processor) needed by subsequent image reconstruction are reduced, the cost of a system is reduced, the processing complexity of the general processor or the DSP needed by the subsequent image reconstruction is simplified through pipelining processing, and the processing speed of the system is increased.

Description

technical field [0001] The invention relates to the field of image processing, in particular to a robust scratch-type image sequence restoration device. Background technique [0002] With the rapid development of electronic automation design, living biometric authentication and identity recognition are more and more used in people's lives. Fingerprint authentication has the highest reliability and cost-effectiveness in biometric authentication, and has become the current biometric authentication. mainstream. At the same time, the fingerprint collection technology is also developing at a high speed. A sensor with lower cost and smaller size will occupy a huge market. Therefore, the scratch-type fingerprint sensor with the above advantages has become the focus of current research. The scratch-type image sensor has a small collection area, and the resolution of the collected images is small. The acquisition method is to scrape objects larger than the acquisition surface in a ...

AI Technical Summary

Problems solved by technology

[0005] The functions of most of the existing scratch image sensors are limited to only output frame images, and the calculation work of reconstructing the frame images into a complete image needs to be completed by a general-purpose processor or DSP, and this method is not suitable for using scratch image sensors. In terms of obtaining the overall image from the sensor, the cost of a general-purpose processor or DSP with better computing power is relatively high; and due to the serial instruction architecture of the general-purpose processor, its processing speed requires a slower scraping speed, which affects the scraping speed. There are relatively large restrictions on how to use

[0006] Moreover, the existing scratch-type image sensor has a large difference in frame image contrast for image acquisition objects of different properties, such as dry, wet, deep texture, shallow texture, etc., which makes it possible to use a general-purpose processor or DSP to complete image reconstruction. The amount of calculation is further increased, which limits the processing speed of the overall system

[0007] Therefore, the existing image reconstruction system using a scratch-type image sensor has slow speed and poor image reconstruction effect. Due to the limitations of the reconstruction algorithm, the reconstructed image sometimes has obvious image misalignment, image deformation, Phenomena such as missing image information and redundant image information

Images