Object Identification App Android Mobile †Myassignmenthelp.Com

Question: Discuss About The Object Identification App Android Mobile? Answer: Introduction: The object identification or image processing app recognizes objects in any photo that is taken using an android phone. Various mobile operators have been providing different plan in Australia. Hence the image processing plan for android phones would be developed proposing a plan for project execution (Sonka, Hlavac Boyle, 2014). The report describes the image processing with the device capability requirements. A brief architecture for the application is also analyzed. Lastly a use case and a class diagram are illustrated along with the proposed user interface and interaction. The Object Identification App: The image processing could be referred as the every possible activity done on any image. This could include cropping of image, increasing the scaling or contrast. Since the digitalization of the images arose in the technology world, there has been high demand for the object recognition (Owen, 2014). The object identification had been a classical problem in the image processing. The computers cannot retrieve objects from any image unlike the human beings. An image consist various pixels for a computer. The artificial intelligence needed to identify objects in the matrix is to be developed by a programmer. Thus the most current approaches for this issue apply for particular objects. Instances of this includes the recognition of optical character transforming images into texts, identification of human faces, pose estimation to determine the position and orientation of any object and the image retrieval based on content to find the image in broader set of the images (Wang et al., 2017). The device capability requirements: The device must comprise of some APIs embedded in the framework of application. They are described hereby. The first one is the location manager allowing receiving every geographical information. Using the GPS, it can recognize the location in details. It determines the position on the basis of available resources (Saipullah, 2013). Next, the XMPP service is utilized for sending data messages to a running user. It acts with any Gmail account. Thus there is no need to create any server infrastructures. Then the notification managers is used that helps in adding notifications to status bar. Lastly the view systems helps in allowing embedded html content in the application. Architecture of the object identification application: The android is to be designed for the complete stack of Applications, middleware and OS. It must be using Linux 2.6 Kernel. The subsequent level must comprise of the libraries. They must be written in C or C++ and serve the most of the central power of the platform. The SGL ad OpenGL|ES are the graphic libraries of the system. They are the 3D and the 2S library respectively (Bucerzan Ra?iu, 2016). The next component has to be the media framework. It would contain most of the codes required to management the most important media formats like AAC, MPEG4 and MP3. Regarding data storage, the SQLite system has to be used. The Android Runtime must be located at the same level. It contains the Dalvik Virtual Machine most vital sections of the android. It uses the Dex-files, the byte-codes originating from conversion of .jar-files during build-time. Here the core libraries could be found containing every collection utilities, classes, IO and so on (Erden et al., 2016). The application framework has to been written in Java. This is the toolkit used by every application. The application like activity manager controls the life cycle of every application. The package managers records the track of the applications installed in the device (Saxena, Jain Singhal, 2014). The Window manager has been the JPL abstraction at the upper level of the services of lower level given by Surface manager. The telephony manager comprises of the APIs regarding the phone applications. The content provider is to form the framework allowing applications for sharing with the other applications. The Use case and class diagrams: The actors in the use case are the user. The user man access he main menu and from there he can edit the image. The edit image uses the log edits which further uses the view edit log. The adjust saturation, adjust contrast, zoom, scroll image and adjust noise includes the edit image. The fix blur also includes the edit image and uses the direct blur. The class diagram is the static structure diagram displaying the structures like user, system, camera controller and others with the attributes and the relationship among them. The proposed user interface and interaction: Like most other apps, the chosen app also requires the GUI or Graphical User Interface for allowing the user interaction. Basically the GUI for the interface is divided in three main areas. The first is the menu bar. This allows the creation of a new museum dataset, saving the current data, and generating future archive files which could transfer XML, HTML and multimedia content like images, movies or audio at once to the telephone (Lord, Rhoads Rodriguez, 2014). This could be useful in a real museum where a user could just download the package and the application. The left-hand area is the next section of the GUI on the main screen. This must be the image list in the present database with the identifier, title per painting and a thumbnail. Below this list, the administrator is able to delete the chosen image or create another new image. Through the selection of the image, the right-hand side of the window would get filled in. Besides the user interface the management interface also needs to perform some work.) Conclusion: The suggested application has been introduced in the report keeping all its usage and potential in the current market place in mind. Next it helps to understand the detail description regarding its architecture. The report has also covered the succinct assessment of the capabilities of the device fulfilling the requirements of the apps. The use case diagram is prepared displaying all its components. The class diagram helps to consider all the classes with relevant links. Lastly an interface is proposed which is attractive, intuitive, and friendly with relevant user interaction with this application. References: Bucerzan, D., Ra?iu, C. (2016). Image Processing with Android Steganography. InSoft Computing Applications(pp. 27-36). Springer, Cham. Erden, F., Velipasalar, S., Alkar, A. Z., Cetin, A. E. (2016). Sensors in Assisted Living: A Audit of signal and image processing methods.IEEE Signal Processing Magazine,33(2), 36-44. Lord, J. D., Rhoads, G. B., Rodriguez, T. F. (2014).U.S. Patent No. 8,855,712. Washington, DC: U.S. Patent and Trademark Office. Owen, S. (2014). zxing-Multi-format 1D/2D barcode image processing library with clients for Android, Java. Saipullah, K. M. (2013). Measuring power consumption for image processing on android smartphone.American Journal of Applied Sciences,9(12), 2052-2057. Saxena, A., Jain, D. K., Singhal, A. (2014, April). Hand gesture recognition using an android device. InCommunication Systems and Network Technologies (CSNT), 2014 Fourth International Conference on(pp. 819-822). IEEE. Sonka, M., Hlavac, V., Boyle, R. (2014).Image processing, analysis, and machine vision. Cengage Learning. Wang, W., Bai, X., Chu, X., Jiang, H., Jia, B., Yang, Y., Kimuli, D. (2017). 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