MV all set to domesticate the service bots

Machine Vision is a term coined to explain the phenomenon of a computer’s ability to read and react to its surroundings. Examples of this technology can be witnessed everywhere, from the automated assembly lines of a factory, to the Virtual Reality gears, to Augmented reality projects and even facial recognition technology. Due to the advent of compact ICs and silicon processors, the power of algorithm computation has improved significantly, rendering a prolific ground for Artificial intelligence. Machine learning has proved to have developed up to 99 percent accuracy and a lesser mistake margin in comparison to the human reflex towards visual stimuli.

A more coherent definition of Machine Vision is the explanation of different types of software and programming languages employed in the process of creating viability for image processing. This visual identification bias has granted machines with an elementary sense of sight. A few of the most subliminal lines of machine vision are listed here under :

1. Autonomous Vehicles:

A not too distant mission of the leaders in the automobile industry like Tesla, BMW, Volvo and Audi is to commercially launch a fully automated automobile navigation. The idea is to integrate the average navigation software of a vehicle with several cameras and geo-location programmes like radar, lidar and ultrasonic sensors, in a pursuit to achieve a self-driving car. These cars should be able to freely navigate, drive passengers, comply with the traffic rules and park-safely without the interference of a human pilot.

Following techniques of Machine Vision can be flagged under Autonomous Vehicle platform :

* 3D Mapping

The concept of 3D mapping is to create a synthetic understanding of roads, lanes and streets in real time. Since the dynamics of a busy road is an ever changing variable. The automobile MV has to be equipped with the ability to create, read and react to all navigation routes and travel obstacles, with passable accuracy. The programmers are hoping to generate and implement algorithms than can predict and eradicate road accidents alongside 3D mapping models in future.

* Object Detection

In addition to detection of objects as a potential obstacle, Machine Vision have aided the capability of self-driving car’s object distinction detection. By taking into account the input data via the LiDar, ultrasonic sensors and cameras and information figures from the navigation satellite system can be incorporated for better results.

* Autonomous Vehicle Training Algorithms

The central processing of Machine Vision lies within algorithms evaluation junctions. There is a wide array of data complied with the help of sensors, cameras and geo-location units, with which the vision of MV is enable the automobile to create a mock comprehension of the present roadblocks, paths and its precipitants and further constitute viable crucial decisions within critical response time.

2. Facial Recognition:

Intelligence agencies around the world and law enforcement bodies have been known to develop and utilize facial recognition technology, for criminal profiling for decades. It is only up until recent times when the social media virtuoso Facebook introduced it on a public level for the first time. Inspired by the study of cranium anatomy and art of reconstructing face, The Facial recognition MV can detect the specific points on nose, eyes, mouth, eyebrows, chin, forehead and carry out more sophisticated operations for the users. Today facial recognition technology is utilized in phone-locks, app-locks and formal registration as a highly effective security assessment. There has been a great deal of media hype over the controversial screening methods at airports and CCTV monitoring, which can even capture the image through a covered/veiled product of MV progression in Facial recognition technology. 

3. Healthcare:

There are several health care apps and gadgets available online for monitoring our carbs intakes, calorie burns and blood pressure readings. Prior to the personalization, the conventional medical practitioners were already depending on X-ray machines, CT scans, mammography and other technological tests to make the final diagnosis, Machine Vision is willing to step in and develop an ability to create a cost effective and personalized method for conducting and reading these tests. There is still a lot of work to be done for achieving surgical refinement equipment and amalgamation of nanotechnology with edible medicine. Machine Vision is helping humanity ascend one step further to this reality.

4. Agriculture & Automated Harvesting:

Harvesting is a greatly strenuous labor, the rigorous amount of hard work required often omits the room for refinement in the process. However many tech-biologists like John Deere are working on creating a high-end product by the way of introducing MV into harvesting. In a demonstration at 2019 CES John and his team presented a dominantly combined automatic harvester with an AI aptitude to locate the best harvest routes by examination of seed germination quality.

With the help of Machine Vision the ordinary harvest machines and processes like weeding and herbicide spraying can be performed with a refined accuracy, so as to minimize the collateral damage on the crops, and assimilating a better yield in terms of quality and quantity. 

5. Manufacturing:

Machine Vision has been waged in the manufacturing sector for a long time on a massive scale, especially with the FMCG sector. The Process of creating perfected products through monitoring and maintenance of chemical compositions, temperature and pressure controls and concentration evaluations is merely a primary phase. MV is applied on the labeling, filling and QA checks of the products, all the way to the storage facility for expiration records, logistics line-ups and incubation. Machine Vision has helped manufacturers in reducing costs and increasing productivity by leaps.

6. Robotics:

Robotics is the most sought after branch of Machine Vision, being able to provide the machine a human-like attire and have it perform as an independent entity, would seem like a sci-fi fantasy only a decade ago. Today there are countless manifestations of robots escorted by Machine Vision technology. Nevertheless it possesses all the more boundlessly complex aspect for MV experts. Robotics is said to assemble all the nano-scopic fields of MV into a singular scope. Though it is still in its rudimentary stages of identifying objects and learning to navigate without supervision. The future of robotics presents humanity with unlimited possibilities.