Computer vision uses digital images and digital models to train computers and have an understanding about the visual world. Computer vision, together with the help of deep learning models, performs accurate identification and classification of objects. Today there are several factors which have made computer vision to grow rapidly. These factors include firstly the use of mobile technology with camera which has made photos and videos readily and abundantly available. Secondly, the hardware and the computing power required for computer vision is easily available, accessible, and affordable today.
Computer vision possesses better visual abilities than humans, be it face recognition or live action processing of any cricket match. It is used across industries. Computer vision (CV) basically works in three steps. Firstly, an image is acquired in real time. Large data sets of images, videos are acquired for analysis. Secondly the image is then processed by making use of deep learning models. Deep learning models are trained by supplying them thousands of pre-defined or labelled images. Thirdly, once the deep learning model is trained, an object is then classified or identified. Today, Artificial Intelligence (AI) is also capable of understanding the image. The various steps involved in computer vision includes Image segmentation, object detection, facial recognition, edge detection, pattern detection, image classification and feature matching. Simple CV applications use only some of the above steps, but advanced applications make use of multiple operations to perform the tasks.
With the help of CV, anomalies can be found out quicker and more accurately compared to human eye. CV can help to detect manufacturing defects quickly and more accurately, which are not easily detectable by human eye. Drones aided with CV can help to detect spills and leakage from pipelines and avoid accidents. CV helps customers by detecting fake goods and products. With the help of CV, crop yield can be optimized by detection of early signs of plant disease. Insurance fraud can be easily spotted as CV helps to distinguish between real and staged auto damage. CV helps in protecting endangered species by monitoring wildlife by footprint identification technique. Footprint images are gathered, and CV software helps in providing information regarding endangered species. CV is being extensively used in health by diagnosing infections from X-ray/CT scans. CV is being used in retail by performing inventory management. Connected and autonomous cars are making best use of Computer vision for tracking facial expression, reducing the occurrence of serious and fatal road accidents, and saving many lives. Computer vision not only enhances computer experiences, but also increases security and reduces the expenses in different spheres of life.
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