Object detection and recognition is an important task in many computer vision applications. In this paper an Android application was developed using Eclipse IDE and OpenCV3 Library. This application is able to detect objects in an image that is loaded from the mobile gallery, based on its color, shape, or local features. The image is processed in the HSV color domain for better color detection. Circular shapes are detected using Circular Hough Transform and other shapes are detected using Douglas-Peucker algorithm. BRISK (binary robust invariant scalable keypoints) local features were applied in the developed Android application for matching an object image in another scene image. The steps of the proposed detection algorithms are described, and the interfaces of the application are illustrated. The application is ported and tested on Galaxy S3, S6, and Note1 Smartphones. Based on the experimental results, the application is capable of detecting eleven different colors, detecting two dimensional geometrical shapes including circles, rectangles, triangles, and squares, and correctly match local features of object and scene images for different conditions. The application could be used as a standalone application, or as a part of another application such as Robot systems, traffic systems, e-learning applications, information retrieval and many others.
翻译:在许多计算机视觉应用程序中, 检测和识别对象是一项重要任务 。 在本文中, 使用 Eclipse IDE 和 OpenCV3 库开发了一个安卓应用程序。 此应用程序能够检测移动画廊根据其颜色、 形状或本地特征装入的图像中的物体。 图像在 HSV 色彩域中处理, 以更好地检测颜色。 使用 Douglas- Peucker 算法检测圆形形状和其他形状。 BRISK ( 硬性坚固的可缩放关键点) 在开发的安卓应用程序中应用了本地特性, 以匹配另一场景图像中的物体图像。 描述拟议的检测算法的步骤, 并演示了应用程序的界面。 应用程序在银河S3、 S6 和 Note1 智能手机上移植和测试。 根据实验结果, 应用程序能够检测11种不同的颜色, 检测两个维度的几何形状, 包括圆形、 直角、 三角和正方形, 并正确匹配对象和场景图像的本地特征。 。 应用程序可以用作不同条件的移动系统,,, 以及其它系统 的检索系统 。, 可以 应用, 可以作为其他系统 。,, 用于 的系统 的系统 的系统 以及其它系统 。