Image features

Features are parts or patterns of an object in an image that help to identify it. For example — a square has 4 corners and 4 edges, they can be called features of the square, and they help us humans identify it's a square. Features include properties like corners, edges, regions of interest points, ridges, etc.

1. What is the purpose of image feature?
2. What is local features of an image?
3. What features are used in image processing?
4. What are high level features of an image?

What is the purpose of image feature?

Image features, such as edges and interest points, provide rich information on the image content. They correspond to local regions in the image and are fun- damental in many applications in image analysis: recognition, matching, recon- struction, etc.

What is local features of an image?

What Are Local Features? Local features refer to a pattern or distinct structure found in an image, such as a point, edge, or small image patch. They are usually associated with an image patch that differs from its immediate surroundings by texture, color, or intensity.

What features are used in image processing?

Contouring, image sharpening, blurring, embossing and edge detection are typical image processing functions (see Table 4.1). Low and high pass filters (spatial filters) are used when the filtering is based on pixel values and gradients to smooth and reduce noise and details.

What are high level features of an image?

Low-level features include edges and blobs, and high-level features include objects and events. Loosely, the low-level feature extraction is based on signal/image processing techniques, while the high-level feature extraction is based on machine learning techniques.