With the rapid development of the security technology industry, biometrics technology has attracted more and more attention from enterprises, manufacturers and even ordinary consumers by virtue of its security, convenience and uniqueness of certification, especially in recent years. The privacy of mobile terminal products is highly valued, which stimulates the market development potential of biometric technology. According to the "2015-2020 China Integrated Circuit Industry Market Demand Forecast and Investment Strategic Planning Analysis Report" released by the Prospective Industry Research Institute, combined with fingerprint recognition of 50% penetration rate on smartphones and tablets, China's fingerprints for the whole year of 2013 The size of the identification chip is estimated to be 3.5 billion yuan, a year-on-year increase of 35%. Therefore, major technology manufacturers, especially semiconductor manufacturers, attach great importance to the research and development of products and technologies in this field. As a leading company in the semiconductor industry, ADI is paying more attention to the great value embedded in the biometrics technology market. Market potential and provide customers with a wealth of product selection and technical support.
At present, the physiological features used in commonly used biometrics technology mainly include face, fingerprint and iris, which is believed by Mr. Zhang Tiehu, technical marketing manager of Analog Devices, a leading global provider of high-performance signal processing solutions. He conducted detailed comparisons and comments on three different biometric technologies.
The first is facial recognition technology. Mr. Zhang Tiehu said that the technology is a physiological identity-based identity authentication technology. Compared with the traditional identity authentication technology based on passwords and IC cards, it is not easy to forge, easy to steal, or Features that will be forgotten; while face recognition is more non-invasive and easy to collect than fingerprint, iris, palmprint recognition and other physiological feature recognition technologies. Therefore, face recognition is a very natural and friendly biometric identification authentication technology.
For the fingerprint recognition technology that is increasingly widely used, Mr. Zhang Tiehu also agrees with the technical value and development potential of it. He also introduced from the perspective of professionals that the fingerprint recognition technology mainly compares the characteristics of different people's fingerprints. Different points to distinguish the identity of different people. The fingerprint recognition technology usually consists of three parts: preprocessing the fingerprint image; extracting the feature values ​​and forming the feature value template; and comparing the fingerprint feature values.
Finally, Mr. Zhang Tiehu also believes that its future technology development prospects are very promising for the biosensing technology that is just emerging, and it is not very extensive compared to facial recognition and fingerprint recognition technology. However, with the failure of the Flom and Safir patents in 2005 and the availability of iris datasets in CASIA and ICE2005, the research on iris recognition algorithms is growing.
ADI has developed many industry-recognized products and solutions on the biometric product line. In this interview, Mr. Zhang Tiehu specifically mentioned the Blackfin series of ADI's star products. He introduced this as a special category. A new 16- to 32-bit embedded processor designed to meet the computational and power constraints of today's embedded audio, video and communications applications. Based on the Micro Signal Architecture (MSA) jointly developed by A DI and Intel, the Blackfin processor combines a 32-bit RISC instruction set with dual 16-bit multiply-accumulate (MAC) signal processing with a general-purpose microcontroller. The ease of use is combined. This combination of processing features enables the Blackfin processor to perform well in both signal processing and control processing applications - eliminating the need to add a separate heterogeneous processor in many cases. This capability greatly simplifies the hardware and software design implementation tasks. Currently, Blackfin processors offer up to 500MHz performance in a single core product. The new symmetric multiprocessor members in the Blackfin processor family doubled their performance at the same frequency. The Blackfin processor family also offers industry-leading power performance down to 0.8V. This combination of high performance and low power is essential for today's and tomorrow's signal processing applications, including broadband wireless, Internet tools with audio/video capabilities, and mobile communications.
The Blackfin processor has the following features:
(1) High performance processor core. The Blackfin processor architecture is based on a 10-level RISC MCU/DSP pipeline and a hybrid 16/32-bit instruction set architecture designed for optimal code density, which is well suited for full signal processing/analysis capabilities. This architecture makes complex digital signal processing operations in face recognition easy to implement on Blackfin.
(2) High bandwidth DMA capability. Face recognition requires manipulation of image blocks, which involves memory data access. Blackfin's DMA controllers automate data transfers with minimal processor core overhead. This can use the computing power of valuable processors for face recognition calculations, reducing the impact of data access on performance.
(3) Video instructions. The most common operation in face recognition is to process pixel values. The Blackfin processor has inherent support for 8-bit data and the word length commonly used by many pixel processing algorithms, greatly improving the processing speed of face recognition.
(4) Hierarchical memory. Blackfin has L1 Cache and L2 Cache two-level Cache. Because Cache has faster access speed than external storage, you can put computationally intensive code in L1 Cache or L2 Cache during face recognition. Effectively increase processing speed.
The Blackfin processor features above indicate that the Blackfin family of processors is ideal for processing biometrics that require high performance computing power and high data throughput.
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