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【2020 Solutions】 Point Media Technologies Introduces Image Quality Monitoring System for High Quality Images at Only One-tenth of the Cost

Video surveillance products generally only provide a black screen for comparison. Whether an image has mosaic or snowflakes can be determined by using the xception model for image quality monitoring, and the application of AI for determination allows the product to stand out.

Implementation of smart identification to monitor streaming in real time

Point Media Technologies is a company that specializes in the development and manufacturing of video streaming products, and has achieved good results in the radio, television, and OTT fields. The start-up coincided with the transition from analogue to digital television in Taiwan in 2013. Taiwan’s radio and television industry has always used foreign products, and not many products were developed by Taiwan This market gap led to the establishment of Point Media Technologies.

Video surveillance products generally only provide a black screen, video without audio, and audio without video, providing real-time images for determining mosaic. Whether an image has mosaic or snowflakes can be determined by using the xception model for image quality monitoring, and the application of AI for determination allows the product to stand out.

Illustration of viewing audiovisual products

▲Illustration of viewing audiovisual products

Image quality monitoring can be used in audiovisual transmission to assist in quality monitoring. At present, channel transmission operators use three methods are used for audiovisual transmission: satellite, data line and Internet public network transmission.

The audiovisual transmission process goes through many encoding and decoding devices. The operation process of these devices may cause damage to the image. In the past, poor signal quality was only discovered after outputting images to the user end. The inspection and repair process also takes a lot of time, resulting in poor viewing performance.

Due to the low cost of using AI for determining image quality, it can monitor each audiovisual node. Once the system detects an error signal, it can notify the engineer immediately to deal with it, reducing the processing time and is better able to improve user satisfaction with the viewing experience.

High-quality audiovisual effects at only one-tenth the cost?

To achieve the high image quality required by radio and television, it often costs up to NT$1 million to purchase related equipment. After the introduction of AI technology, the cost is only NT$100,000, which is only about one-tenth of the cost. The AI audiovisual determination module has a multi-screen monitoring system. After commercial verification, this AI image quality determination module is able to assist automated monitoring and improve the quality of audiovisual transmission. If this AI module program is applied to a microcomputer, it will be more convenient to introduce it to various user units. All radio and television, OTT, and live streaming operators can use this system to meet their automated monitoring needs. The AI module can detect image problems with an accuracy of about 96%, allowing problems to be quickly detected and resolved.

System architecture chart

▲System architecture chart

Channel transmission operators are responsible for the reception and transmission of dozens of channel signals in Taiwan. The audiovisual signals received will be transmitted to various cable TV and OTT platforms in Taiwan. Since each channel needs to be transmitted to many nodes, the TV wall in the monitoring center is full of TV signals. Manual monitoring is imperfect, resulting in line abnormalities and unstable signal quality, which in turn affects the viewers’ rights. After introducing the system, the image quality monitoring system replaces manual monitoring and immediately reports any abnormalities in the image, greatly improving the quality of audiovisual transmission.

Dual mode error event examination

▲Dual mode error event examination

Point Media Technologies stated that the system is currently only able to monitor defects, snowflakes, mosaic noise, gap compensation, and jitter. It is not yet able to automatically adjust quality, which will be the greatest challenge for future monitoring systems.

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