Development of An Android Application for Object Detection Based on Color, Shape, or Local Features
Lamiaa A. Elrefaei, Mona Omar Al-musawa, Norah Abdullah Al-gohany

TL;DR
This paper presents an Android app that detects objects using color, shape, or local features, leveraging OpenCV and tested on various smartphones, demonstrating effective detection of colors, shapes, and feature matching.
Contribution
The paper introduces a mobile application capable of multi-faceted object detection using color, shape, and local features, implemented with OpenCV on Android devices.
Findings
Detects eleven colors accurately
Identifies multiple geometric shapes including circles and rectangles
Successfully matches local features between images
Abstract
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…
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