FREMONT, CA: Machine vision is one of the important additions to the manufacturing sector. It has provided automated inspection capabilities as part of QC procedures. Nevertheless, the world of automation is becoming more complex with time. With rapid developments in many different areas, such as imaging techniques, robot interfaces, CMOS sensors, machine and deep learning, embedded vision, data transmission standards, and image processing capabilities, vision technology can benefit the manufacturing industry at multiple different levels. New imaging techniques have brought new application opportunities.
Our solutions provide automated analysis of millions of real-time and retrospective imaging studies. This allows early identification of disease, and implementation of decision support tools for population health and risk management. Our development team and our dedicated partners are creating the hundreds of algorithmic tools and insights needed to bring clinical diagnostic support to the next level. A sample of our algorithms can be seen here, with a multitude of additional insights planned for release over the coming months.
Imaging in three dimensions rather than two offers numerous advantages for machines working in the factories of the future by granting them a whole new perspective to view the world. Combined with embedded processing and deep learning, this new perspective could soon allow robots to navigate and work in factories autonomously by enabling them to detect and interact with objects, anticipate human movements and understand given gesture commands. Certain challenges must first be overcome to unlock this promising potential, however, such as ensuring standardisation across large sensing ecosystems and increasing widespread understanding of what 3D vision can do within industry. Three-dimensional imaging can be achieved by a variety of formats, each using different mechanics to capture depth information. Imaging firm Framos was recently announced as a supplier of Intel's RealSense stereovision technology, which uses two cameras and a special purpose ASIC processor to calculate a 3D point cloud from the data of the two perspectives.
The increased sophistication of artificial neural networks (ANNs) coupled with the availability of AI-powered chips have driven am unparalleled enterprise interest in computer vision (CV). This exciting new technology will find myriad applications in several industries, and according to GlobalData forecasts, it would reach a market size of $28bn by 2030. The increasing adoption of AI-powered computer vision solutions, consumer drones; and the rising Industry 4.0 adoption will drive this phenomenal change. Deep learning has bought a new change in the role of machine vision used for smart manufacturing and industrial automation. The integration of deep learning propels machine vision systems to adapt itself to manufacturing variations.
"At Altek, we are constantly striving to enhance our digital image solutions and set the direction for the future of smarter imaging devices," said Jason Lin, General Manager and Corporate Senior Vice President of Altek. "CEVA's imaging and vision DSP provides the platform which allows us to further enhance the image quality of our solutions and push the boundaries of what a camera can do using artificial intelligence and advanced vision algorithms." "Altek is a proven leader in imaging, with a strong track record in the smartphone space and we are excited to work with them," said, Ilan Yona, vice president and general manager of CEVA's Vision Business Unit. "The combination of Altek's advanced imaging technologies along with our DSP-based vision and machine learning offering creates one of the most intelligent digital imaging solutions on the market today." CEVA's latest generation imaging and vision DSP platforms address the extreme processing requirements and low power constraints of the most sophisticated machine learning and machine vision applications used in smartphones, surveillance, augmented reality, sense and avoid drones and self-driving cars.