The research institute has developed a hand-jitter signal estimation algorithm with the best compensation effect, and a fuzzy logic (Fuzzy Logic) controller with low computational load and easy implementation, which can greatly improve the stability of the lens module of the mobile phone and improve the voice coil motor. The hysteresis effect will help the optical anti-shake technology to expand into the mobile phone market.
Optical anti-shake technology
Figure 1 shows a miniature camera module with optical image stabilization. The most representative technology of the anti-shake system is Electronic Image Stabilizer (EIS) and optical image stabilization technology. Among them, the electronic anti-shake technology uses image processing to prevent image blur. The electronic anti-shake effect depends on the design and efficiency of the algorithm. The system does not need to add additional hardware, which is suitable for miniaturization design, but usually must sacrifice image resolution. Rate (or image size), which is its main drawback.
　　 Figure 1 Image sensor and optical image stabilization module
The optical image stabilization technology is divided into two types: Sensor-shift Optical Image Stabilization and Lens-shift Optical Image Stabilization (Fig. 2). The optical image stabilization system utilizes an optical lens set (Lens). Or the movement of the Image Sensor to compensate the user's hand shake, so the image resolution will not be sacrificed, and the added value of the product will be greatly improved.
　　 Figure 2 Schematic diagram of optical anti-shake system; (A) optical anti-shake system for image sensor movement; (B) optical anti-shake system for lens movement.
Hand jitter signal estimation technique
Optical image stabilization requires additional actuator design, so key key technologies include controller design and user hand vibration signal estimator design. The hand shake signal estimator algorithm uses a MEMS inertial sensor mounted on a smart phone to sense a shaking signal generated by a hand when a user shoots, and drives a precision voice coil motor driven by a miniature camera module via a closed loop control system to compensate the user. Shake caused by the hand to avoid blurring of the captured image. The jitter signal estimator includes inertial sensors (multi-axis gyroscopes and accelerometers) and inertial sensing signal processing algorithms. The South Branch of the Industrial Technology Research Institute has invested in the development of inertial signal estimation technology for many years, and has successfully applied it to pedestrian/travel inertial navigation and optical image stabilization systems, and has achieved considerable results.
After the hand-shake signal estimator senses the hand-shake signal by using the gyro component, the trembling angle signal can be obtained through digital signal processing and integral calculation. After the experimental measurement and analysis, the general hand vibration frequency characteristic main frequency band is 2~12 Hz. Therefore, the signal processing algorithm also designs the filter for the signal characteristics of the frequency band. The developed algorithm uses the first-order low-pass filter and the high-pass filter to filter out the high-frequency noise signal and the low-frequency active signal. The user operates the signal generated by the camera).
The low-pass and high-pass filters can compensate for the jitter signal of a specific bandwidth, and can avoid the phase delay caused by the filter to the signal, so that the signal processing algorithm and the control system can be integrated to obtain the best compensation effect, so that the anti-shake module Can achieve the expected performance. The algorithm considers the phase change of the jitter signal caused by the filter, so the adaptive hand jitter estimator developed by this method can obtain accurate hand jitter estimation signal in the wide-band domain. Figure 6 is a block diagram of the jitter signal estimator.
　　 Figure 3 Hand jitter signal estimator block diagram
Optical anti-shake controller design
The key technology of another optical image stabilization system is the controller design. Most of the miniature camera module actuators use voice coil motors, but they have nonlinear characteristics such as hysteresis, friction and time-varying parameters. Therefore, controller design must be considered. To the nonlinear characteristics and the computational load at the time of implementation. Fuzzy Logic Controller has many advantages such as low computational load, no need for accurate mathematical model of controlled system, easy implementation of architecture and effective compensation of nonlinearity of microactuator. In recent years, ITRI South Branch The developed optical image stabilization system successfully uses the fuzzy controller to drive the voice coil motor, thereby compensating the displacement compensation signal calculated by the hand shake signal estimator algorithm to achieve the anti-shake effect. The optical image stabilization system is shown in Figure 4.
　　 Figure 4 Optical image stabilization system block diagram
Anti-shake performance verification
At present, the anti-shake performance on the market is mainly divided into 1~4 levels. In general, the anti-shake performance level is estimated by the magnification of the safe shutter speed, which is equal to the shutter length of one second of the focal length. For example, if the focal length of the lens is 40 mm (mm), then The speed of the safety shutter is 1/40 second. Use a clear image below the safe shutter speed. The anti-shake level is the magnification of the safe shutter speed. If the safe shutter speed is 1/40 second, for example, the anti-shake Performance level 4 means that the camera can still capture clear images at (1/40)×2^4=1/2.5 second shutter speed, and the image clarity can be less than the Stabilization Rate (SR). -15dB or ISO-12233 to identify Image Sharpness.
Among them, the stability rate experiment is mainly based on the optical anti-shake system in the case of vibration compensation and no vibration compensation, the fixed shutter time condition determines the shooting test target, and the anti-shake performance is evaluated by the ratio of the image vibration pixel (height) on the photographed photo. See Figure 5 for a description of the stability rate.
　　 Figure 5 Anti-shake stability rate definition map
OISOFF_S represents the image pixels (vertical height) captured when the optical image stabilization system is turned off and the camera is used when the camera is shaken; OISON_S represents the image pixels (vertical height) captured when the optical image stabilization system is turned on and the camera shake is generated. ; OISOFF_NS represents the image pixel (vertical height) captured when the OIS system is stationary when the optical image stabilization system is turned off and no hand shake is generated. The adaptive optical image stabilization system developed by the South Branch of the Industrial Technology Research Institute has reached the market-level four-level anti-shake performance.
With the development of new design miniature camera modules for MEMS inertial sensors and mobile phone camera modules, the motion sensing and anti-shake technology of smart phones has become increasingly important. At present, the micro camera module on the market mostly uses voice coil motor as the main actuator. With the development of technology of smart phone and inertial sensor, the future optical image stabilization technology will gradually gain attention, and it will be one of the functions of high-end smartphones on the market. .
Inertial sensing / anti-hand shake into standard equipped with mobile phone added value is expected to increase significantly
The Institute of South Campus of ITRI has invested in the development of inertial navigation and optical image stabilization cameras for many years. It has extensive experience in mobile phone inertial sensing and optical image stabilization systems. The optical image stabilization system introduced in the article is the result of research and development. Successfully transferred to multiple manufacturers. The market also predicts that the new design of mobile phone camera module and MEMS inertial components will stimulate the growth of integrated MEMS inertial sensor shipments in the consumer electronics application market, and promote the development of optical anti-shake technology. In the future, 6-axis inertia Sensing components (including accelerometers and gyroscopes) and optical image stabilization will become standard equipment for high-end smartphones, greatly increasing the added value of smartphones. It is also an important factor in future market-leading products, for inertial components and miniature camera modules. For manufacturers, it is a very important product development direction.
In recent years, the smart phone market has become more mature and diversified due to the sales of brand products such as Apple, Samsung, and HTC. According to the report of the International Data Information (IDC) of the market, the smartphone market began to show explosive growth in 2010, and it is predicted to reach 1.5 billion in 2017 (Figure 1). At the same time, the micro-electromechanical system (MEMS) inertial sensing component and the high-pixel compact camera module (CCM) on the smartphone have become the standard equipment for high-end mobile phones, and the future motion sensing and optical image stabilization technology. Will greatly enhance the functionality and added value of the product.
　　 Figure 6 Analysis of smartphone shipments from 2012 to 2017
MEMS components/camera modules complement each other to prevent more hand shake
Most of the smart phones on the market have been equipped with MEMS motion sensing components, including accelerometers, gyroscopes (inertial components) and magnetometers. They are currently in line with the design trend of low power consumption, light weight and small size pursued by mobile devices. Widely used in consumer electronics, including 3C products such as pedometers, smartphones and tablets. According to the market research conducted by IHS iSuppli, the market for MEMS motion sensing components of smart handheld devices (including smart phones and tablet computers), the actual revenue in 2013 was about 1.5 billion US dollars, an increase of 12% compared with 2012. It can reach $2.21 billion annually (Figure 2). Market research results indicate that smart phone configuration of MEMS inertial components is an inevitable trend.
　　 Figure 7 Benefits of MEMS motion sensing components for smart handheld devices from 2011 to 2016
In addition to MEMS inertial sensing components, smart phones are also equipped with miniature camera modules. According to IC Insights survey and statistics, global camera module shipments are expected to increase from 2 billion in 2011 to six in 2016. One billion sets. In 2012, the global digital camera and imaging system market was 55.5 billion US dollars. It is predicted that its total output value will reach 77.8 billion US dollars in 2016, of which 30% of mobile phone camera modules (Figure 3), its proportion is gradually rising, and there are Replacing the trend of general digital camera products; IC Insights also predicts that the miniature camera module equipped with smart handheld devices will grow at a rate of 21.9% between 2013 and 2019. From the growing demand for smartphone multimedia functions, changes in user habits, and market research and analysis results, smartphones have gradually replaced digital cameras. High-end smartphones in the market have begun to combine optical camera modules and motion sensing technology to achieve Optical Image Stabilization (OIS) to improve the quality of mobile phone photography. It is expected that the market share of smartphones in the future will be affected by the new design of mobile phone camera modules and optical image stabilization technology.
Figure 8 2016 Digital Camera System Sales Forecast
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