Abstract
Object detection and recognition is one of the important techniques in computer vision for searching and scanning and identifying an object in images or videos. Object detection and recognition enters into many important fields where one of the uses of object detection and recognition is to detect region of injury and determine the type of injury. This paper suggested a new effective method called Local Quadrant Pattern (LQP). The proposed method uses a window and passes it on all pixels of the image and uses the pixel direction to arrange the adjacent pixels. It also uses four code values to encode and then produce a texture feature matrix which is used to detect objects as well as extract features based on magnitude of pixels for image classification. The experiments were conducted on the infected regions in the skin and the results showed the ability of the method to detect regions of infection as well as the high accuracy in the classification of those regions.
Highlights
Object detection is one of the main and important techniques in computer vision and image processing
Local Quadrant Pattern is a new method suggested in this paper
The proposed method has developed previous methods in local patterns where the 3×3 window has been used to get the information of pixel and its neighbors
Summary
Object detection is one of the main and important techniques in computer vision and image processing. F., et al have described an object detection system based on mixtures of multiscale deformable part models by combined a margin-sensitive approach for data-mining hard negative examples with a formalism called latent SVM. Their system is able to represent highly variable object classes and achieves state-of-the-art results in the PASCAL object detection challenges [4]. The extracted features are used to classify the image as normal skin or melanoma cancer lesion [9]. Algorithm is proceeding to extract the features of ABCD attributes Techniques used in this method combine existing methods with new methods to detect color asymmetry and dermoscopic structures [10].
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