Auto-adjustment of image produced by multi-transducer ultrasonic system

Acoustic microscopy is characterized by relatively long scanning time, which is required for the motion of the transducer over the entire scanning area. This time may be reduced by using a multi-channel acoustical system which has several identical transducers arranged as an array and is mounted on a mechanical scanner so that each transducer scans only a fraction of the total area. The resulting image is formed as a combination of all acquired partial data sets. The mechanical instability of the scanner, as well as the difference in parameters of the individual transducers causes a misalignment of the image fractures. This distortion may be partially compensated for by the introduction of constant or dynamical signal leveling and data shift procedures. However, a reduction of the random instability component requires more advanced algorithms, including auto-adjustment of processing parameters. The described procedure was implemented into the prototype of an ultrasonic fingerprint reading system. The specialized cylindrical scanner provides a helical spiral lens trajectory which eliminates repeatable acceleration, reduces vibration and allows constant data flow on maximal rate. It is equipped with an array of four spherically focused 50 MHz acoustic lenses operating in pulse-echo mode. Each transducer is connected to a separate channel including pulser, receiver and digitizer. The output 3D data volume contains interlaced B-scans coming from each channel. Afterward, data processing includes pre-determined procedures of constant layer shift in order to compensate for the transducer displacement, phase shift and amplitude leveling for compensation of variation in transducer characteristics. Analysis of statistical parameters of individual scans allows adaptive eliminating of the axial misalignment and mechanical vibrations. Further 2D correlation of overlapping partial C-scans will realize an interpolative adjustment which essentially improves the output image. Implementation of this adaptive algorithm into a data processing sequence allows us to significantly reduce misreading due to hardware noise and finger motion during scanning. The system provides a high quality acoustic image of the fingerprint including different levels of information: fingerprint pattern, sweat porous locations, internal dermis structures. These additional features can effectively facilitate fingerprint based identification. The developed principles and algorithm implementations allow improved quality, stability and reliability of acoustical data obtained with the mechanical scanner, accommodating several transducers. General principles developed during this work can be applied to other configurations of advanced ultrasonic systems designed for various biomedical and NDE applications. The data processing algorithm, developed for a specific biometric task, can be adapted for the compensation of mechanical imperfections of the other devices.