What algorithm to use to obtain Objects from an Image

I would like to know what algorithm is used to obtain an image and get the objects present in the image and process (give information ab开发者_运维问答out) it. And also, how is this done?

I agree with Sid Farkus, there is no simple answer to this question.

Maybe you can get started by checking out the Open Computer Vision Library. There is a Wiki page on object detection with links to a How-To and to papers.

You may find other examples and approaches (i.e. algorithms); it's likely that the algorithms differ by application (i.e. depending on what you actually want to detect).

There are many ways to do Object Detection and it still an open problem.

You can start with template matching, It is probably the simplest way to solve, which consists of making a convolution with the known image (IA) on the new image (IB). It is a fairly simple idea because it is like applying a filter on the signal, the filter will generate a maximum point in the image when it finds the object, as shown in the video. But that technique has several cons, does not handle variants in scale or rotation so it has no real application.

Also you can find another option more robust feature matching, which consist on create a dataset with features such as SIFT, SURF or ORB of different objects with this you can train a SVM to recognize objects

You can also check deformable part models. However, The state of the art object detection is based on deep-learning such as Faster R-CNN, Alexnet, which learn the features that will be used to detect/recognize the objects

Well this is hardly an answerable question, but for most computer vision applications a good starting point is the Hough Transform