The Fast Integration of a Rotated Rectangle Applied to the Rotated Haar-Like Features for Rotated Objects Detection
Mohamed Oualla1, Khalid Ounachad2, Abdelalim Sadiq3
1Mohamed OUALLA*, Software Engineering & Information Systems Engineering Team, Computer Sciences Department, Faculty of Sciences and Technology (FST), Moulay Ismail University, Errachidia, Morocco.
2Khalid Ounachad, Information System and Multimedia team, Faculty of Sciences (FS), Ibn Toufail University, Kénitra, Morocco
3Abdelalim Sadiq, Information System and Multimedia team, Faculty of Sciences (FS), Ibn Toufail University, Kénitra, Morocco
Manuscript received on March 15, 2020. | Revised Manuscript received on March 25, 2020. | Manuscript published on April 10, 2020. | PP: 1849-1855 | Volume-9 Issue-6, April 2020. | Retrieval Number: F4349049620/2020©BEIESP | DOI: 10.35940/ijitee.F4349.049620
Open Access | Ethics and Policies | Cite | Mendeley
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the area of Object Detection, the most important step is the extraction of object features. One of the most used approaches is Haar Like features and the Integral Image technique to integrate them. The Integral Image technique, used by Viola and Jones, is generally used to calculate the integral of a rectangular filter in an input picture. This filter is a rectilinear rectangle. We propose a method to integrate a rotated one by any angle of rotation inside an image based on the Bresenham algorithm of drawing a segment. We use some pixels – called key points – that forms the four segments of a rotated rectangle, to calculate its Integral Image. Our method focuses on three essential tasks; the first is to determine the rule for drawing a segment (SDR), the second is to identify all the key points of the rectangle r, and the third is to calculate the integral image. The speed of this method depends on the size and angle of rotation of the rectangle. To demonstrate the efficiency of our idea, we applied it to the rotated Haar-like features that we proposed in a later work , which had as objectives the improvement of the Viola and Jones algorithm to detect the rotated faces in a given image. We performed tests on more widespread databases of images, which showed that the application of this technique to rotated Haar-Like features improves the performance of object detectors, in general, and faces in particular.
Keywords: Haar-Like Features, Integral Image, Face Detection, Object Detection, Viola & Jones Algorithm, AdaBoost.
Scope of the Article: System Integration