Product Details
Macc Series Iris Recognition Accelerator Cards Multiple Models
Available High-Performance Processing Capability
Description
Macc series acceleration card adopts the third generation iris
recognition algorithm Phaseiris™3.0, which is independently
developed by iris recognition technology. There are three models of
MACC.P, MACC.M and MACC.C. Its fast and efficient iris image coding
and comparison processing capabilities can help developers quickly
establish iris databases and realize iris comparison service
deployment, such as applied to iris access control systems.
Macc.p&Macc.m series acceleration card adopts Xilinx A7 series
chip, which can realize fast and efficient iris image recognition
and processing, and can be applied to database acceleration,
machine learning, data analysis and video processing. Macc.c uses
Xilinx K7 series chip, built-in 6 AI core, can support 1 million
people's data fast comparison, up to provide 800,000
template/second comparison processing power.
Functional
- Compared with CPU/ GPU-based solutions, iris image processing
performance has higher data throughput, lower latency, and more
economical cost;
- Up to 50 iris images per second coding speed and 800,000 templates
per second iris data comparison speed, and support multi-card
parallel processing;
- Suitable for X86/ARM/Windows/Android platform systems;
- Support a variety of expansion methods, capacity and performance
can be quickly upgraded;
- Solutions can be deployed interchangeably in the cloud or
on-premises and can be scaled according to application needs;
- Provide multi-platform SDK development kit, convenient for users to
quickly develop;
Specification
Application
In its existing system (embedded or PC), iris recognition can be
quickly realized by adding an acceleration card, which is mainly
applied to equipment manufacturers, integrators, system
manufacturers, solution manufacturers, etc.
Company Profile
Wuhan Homsh Technologies Co., Ltd is one of the few iris
recognition intelligent semiconductor chip suppliers in the world.
It is a national hi-tech company, which has completely innovated
intellectual property rights of its key iris recognition
algorithms.Homsh Technologies is committed to the research,
development, application and industrialization of the core
technology and related products of iris biometrics technology.
Homsh Technologies specializes in advanced AI iris recognition,
FPGA, and ASIC hardware algorithms. We aim to revolutionize global
security and identity verification through continuous innovation.
Our experienced team is committed to delivering unparalleled speed,
accuracy, and flexibility in iris recognition technology. As
industry leaders, we offer cutting-edge solutions that are
future-proof, ensuring your systems are fast, accurate, and
compliant with evolving security standards.
Homsh Technologies is a cutting-edge technology company
specializing in advanced AI iris recognition algorithms, FPGA
hardware implementation algorithms, and ASIC hardware
implementation algorithms. Our core technologies cover a
comprehensive range from highly accurate iris recognition
algorithms to high-speed, low-power hardware solutions. Our goal is
to provide the most advanced and reliable solutions for the global
security and identity verification sectors through continuous
innovation and R&D.
Our team consists of a group of experienced and passionate
engineers, scientists, and experts dedicated to pushing the
boundaries of iris recognition technology. Through ongoing
optimization and refinement of our algorithms and hardware, we are
able to offer unparalleled speed, accuracy, and flexibility to meet
a wide variety of application needs.
Homsh Technologies is changing the game in security and identity
verification. We are not just another tech company; we are
innovators and leaders in the field of iris recognition. By
partnering with us, you will gain access to the most advanced
technologies and solutions, ensuring that your systems are not only
fast and accurate but fully compliant with future security
standards.

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