Image recognition is a technique for acquiring, processing, scrutinize, and sympathizing images. It gathers high-dimensional data from the real world in order to generate numerical or symbolic information. Image recognition uses disentangling of representational information from image data using replica created with the help of geometry, physics, statistics, and learning theory.
Image recognition (biometric-based recognition) technique has emerged as the most promising alternative of card based recognition for identifying individuals in recent past. Image recognition is used for verification (one to one matching) and identification (one to many matching) of individuals.
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Image recognition technologies include identification based on physiological distinctiveness of the people such as facial patterns recognition, fingerprints recognition, hand geometry recognition, hand veins pattern recognition, finger geometry recognition, palm recognition, iris recognition, retina recognition, and voice recognition. Image recognition also identify the behavioral uniqueness of the individuals such as gait, signature and keystroke dynamics
The recognition based on passwords and PINs are trailing in popularity mainly due to the fact that they are hard to remember and cannot be stolen, duplicated by the intruders. Moreover the risk associated with misplacing of cards, tokens, keys and the like is also lend a hand in wide acceptance of image recognition as an alternative of traditional access control systems.
On the basis of technology the global image recognition market can be broadly categories in five different market variants namely, optical character recognition (Ocr), pattern and gradient matching, object recognition, barcode/Qr code recognition and facial recognition.
On the basis of the different component use in the image recognition equipment the overall market can be broadly categorized in three segments namely, hardware, software, and services.
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Based on the end user application the image recognition market can be further categories in eight different classes namely, government and defense, banking, financial services and insurance, healthcare and life sciences, manufacturing or industrial, consumer goods and retail, information technology and telecommunications, transport and logistics and others.
The growing use of face recognition technology in smart phones, tablets and personal computer owing to the advancement in size and accuracy is propelling the market for face recognition technology. Moreover increasing governmental budget towards homeland security and defense is further driving the market in developing countries such as India, China, and Russia. Increasing use of facial recognition access system over card based access system in industries and residence is providing new market opportunities for the facial recognition technology.
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