Features Extraction for Object Detection Based on Interest Point - Amin Mohamed Ahsan; Dzulkifli Bin Mohamad (Indonesian Journal of Electrical Engineering and Computer Science, 2013)
In computer vision, object detection is an essential process for further processes such as object tracking, analyzing and so on. In the same context, extraction features play important role to detect the object correctly. In this paper we present a method to extract local features based on interest point which is used to detect key-points within an image, then, compute histogram of gradient (HOG) for the region surround that point. Proposed method used speed-up robust feature (SURF) method as interest point detector and exclude the descriptor. The new descriptor is computed by using HOG method. The proposed method got advantages of both mentioned methods. To evaluate the proposed method, we used well-known dataset which is Caltech101. The initial result is encouraging in spite of using a small data for training. DOI: http://dx.doi.org/10.11591/telkomnika.v11i5.2508