  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.
