Image Recognition

Image recognition is an application of AI/ML that enables computers to capture and understand images and videos.

Image recognition solutions can identify people, animals, trees, and many such objects around us. Image recognition is a step beyond object detection in that it not only detects an object but is also able to identify and classify it into specific categories. Depending on how powerful the algorithm is and the data set it has for comparison, the level of identification may vary.

For example, an image recognition solution may be able to detect and identify an object as a human but may not be able to identify the gender. Or it may be able to identify a vehicle or go on to identify the type of vehicle, a car, a bike, a truck and so on.

A digital image is composed of picture elements, known as pixels. Each pixel is a numerical value that indicates to the computer what color or shade that pixel should be displayed as. Together these individual pixels form the image we all see and recognise. Image processing algorithms have to read these data values and recognize or match patterns with known images to be able to determine what the image might be.

Image recognition solutions include methods for acquiring, processing, analyzing and understanding digital images and taking appropriate action. The image data can take many forms, such as video sequences, views from multiple cameras, multi-dimensional data from a 3D scanner, or medical scanning devices.

There are several applications of AI/ML-based image recognition algorithms:

• Facial Recognition to identify and authenticate humans.
• Object recognition to assist vehicle driver assist systems.
• Video analysis to identify people and actions.

AWS Rekognition

Amazon Rekognition makes it easy to add image and video analysis to your applications. You just provide an image or video to the Amazon Rekognition API, and the service can identify objects, people, text, scenes, and activities. It can detect any inappropriate content as well. Amazon Rekognition also provides highly accurate facial analysis and facial recognition. With Amazon Rekognition Custom Labels, you can create a machine-learning model that finds the objects, scenes, and concepts that are specific to your business needs.

Amazon Rekognition is based on the same proven, highly scalable, deep learning technology developed by Amazon’s computer vision scientists to analyze billions of images and videos daily. It requires no machine learning expertise to use. Amazon Rekognition includes a simple, easy-to-use API that can quickly analyze any image or video file that’s stored in Amazon S3. Amazon Rekognition is always learning from new data, and we’re continually adding new labels and facial comparison features to the service.

Common use cases for using Amazon Rekognition include the following:

• Searchable image and video libraries: Amazon Rekognition makes images and stored videos searchable so you can discover objects and scenes that appear within them.

• Face-based user verification: Amazon Rekognition enables your applications to confirm user identities by comparing their live image with a reference image.

• Detection of Personal Protective Equipment: Amazon Rekognition detects Personal Protective Equipment (PPE) such as face covers, head covers, and hand covers on persons in images. You can use PPE detection where safety is the highest priority. For example, industries such as construction, manufacturing, healthcare, food processing, logistics, and retail. With PPE detection, you can automatically detect if a person is wearing a specific type of PPE. You can use the detection results to send a notification or to identify places where safety warnings or training practices can be improved.

• Sentiment and demographic analysis: Amazon Rekognition interprets emotional expressions such as happiness, sadness, or surprise, and demographic information such as gender from facial images. Amazon Rekognition can analyze images, and send the emotional and demographic attributes to a data analysis tool for reporting on trends such as customer satisfaction. Note that a prediction of an emotional expression is based on the physical appearance of a person's face only. It is not indicative of a person’s internal emotional state, and Rekognition should not be used to make such a determination.

• Custom labels: With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can find your logo in social media posts, identify your products on store shelves, classify machine parts in an assembly line, distinguish healthy and infected plants, or detect animated characters in videos.

You don’t need computer vision or deep learning expertise to integrate powerful image and video analysis into your apps. With the Amazon Rekognition API, you can easily and quickly build image and video analysis into any web, mobile, or connected device application.