Image annotation has exponentially increased the accuracy of a camera with the help of computer vision and artificial intelligence working in the background, teaming up with machine learning. Read on to know more about the benefits of image annotation to your business.
What is Image Annotation?
Image annotation refers to a process of image labeling as a part of a machine learning model. It helps computers understand the visuals by labeling them with annotation tools, text, or both as per the requirement. It is one of the most important development stages of image recognition applications and computer vision that performs recognition, description, and interpretation of results from digital videos or images. Supervised machine learning models require data labeling to function effectively, as image annotation is like a subset of data labeling. Image annotation requires a manual workforce to determine the labels or tags and transmit image-specific information to the machine learning model being trained. This process can be simply explained as the questions a child asks to explore its surrounding environment.
Techniques of image annotation
There are five profound techniques of image and notation, namely
- Polyline: Online techniques create machine learning models to guide computer vision for autonomous driving.
- Polygon: Polygon is used to frame the ages of an object to pick point objects from images. It is practised to level irregularly shaped objects.
- Masking: Masking refers to pixel-level annotations that hide certain areas of an image to enhance other parts. It is considered a filter that makes it easier to focus on a certain part of an image.
- Landmarking: Landmarking is an effective technique used for facial recognition features. It can identify gestures and facial expressions along with emotions and is also used to mark body orientation and position.
- Bounding box: In this technique, a frame is drawn to surround the object that needs to be identified. It can be used for both three-dimensional and two-dimensional images.
Benefits of image annotation
Image annotation is a form of data entry services. It is helpful for businesses from different industries. It is estimated that the machine learning and artificial intelligence data preparation market will reach 1.2 billion dollars by 2023. As the data suggests, the benefits of image annotation are profound as it assists a wide range of businesses and services.
Image annotation assists deep learning models in improving the effectiveness and accuracy of diagnosis and eventually enhancing the treatment quality. The annotated computer vision data can identify images from MRI, X-ray scans, CT scans, etc. With image annotation, the interpretation of patterns and identification of tumors, hairline fractures, cancers, abscesses, etc. have become easier and more accurate. In addition, image annotation also eliminates the cost of expensive scanners and brings efficiency to health care businesses.
2. Security and Surveillance
Image and notation are tremendously useful in the surveillance and security industry, requiring computer vision models to analyze human behavior, identify faces from the crowd, and much more. It uses 2D or 3D bounding box technique to Mark and tracks a person even from a group. The machine learning model can be further trained to calculate and estimate the number of people in a group, estimate demographics, and several other things.
Image annotation is equally important in e-commerce for an assured customer experience. Annotations label specific keywords and captions to a product to make it easier for the visitor to find the product. It ensures that all products carry the correct information for the correct category in the catalog. It also helps in a better user experience while looking for a specific product with relevant recommendations. This can be better understood with an example where a visitor needs to look for a product but is unsure what to look for in the website’s search bar. In this case, the visitor can simply drag and drop the image to the website search bar, and the machine learning models will go through the repository to find the perfect match for the image.
The introduction of image annotation services has transformed the agriculture sector. Machines annotate plants, crops, fruits, and soil to identify them and take certain actions accordingly. Image annotation helps identify unwanted crops, insects, wildflowers, etc., to ensure a clean surface for better crop growth. It can also be used to detect soil conditions and field health. Moreover, image annotation is also used for geo sensing to determine the soil’s health condition, allowing businesses to select the right crop for the soil.
How to get your image annotation done?
The increasing popularity of image and notation has made the process severely important for businesses from different sectors and industries. The in-house development and image annotation can be heavy on the financial part as well as it is a time taking process. Thus, several businesses worldwide outsource image annotation for efficient and effective results.