Object Detection by Point Feature Matching using Matlab - Bulbul, Mohammad Farhad; Badsha, Faishal; Islam, Rafiqul (European Journal of Applied Sciences, 2019)
Objects detection is an important part in image processing field. For detection object at first we take a photo called test image and then detect some region or point on the image and compare it with reference image. For this task, we use an algorithm that is used in many computer vision applications and is also considered very fast by compared to others. This algorithm can detect and describe local features for any interest object and extract features or descriptor points from it and compare it with the features that extracted from original image. Matching process is done among features and decision is made based on similar features found. This algorithm is called Speeded up Robust Features (SURF) algorithm. In this paper, we use the SURF algorithm which can detect the position of the interest object in original image by using geometric transform. This object capturing method works best for objects that exhibit in a cluttered texture patterns. When a part of object is occluded by other objects in the scene, in this case we use this algorithm to find reference image.