Introduction To Android

Android is a Linux-based operating system for mobile phones such as smart phones and tablet computers. Android provides an open platform to developers for creating their own applications for use by a variety of mobile devices. Initially, Google Inc.. buy Android Inc.., newcomers who make software for mobile phones. Then to develop Android, formed the Open Handset Alliance, a consortium of 34 companies for hardware, software, and telecommunications, including Google, HTC, Intel, Motorola, Qualcomm, T-Mobile, and Nvidia.

At the inaugural release of Android, 5 November 2007, with the Open Handset Alliance Android states support the development of open standards on mobile devices. On the other hand, Google released the Android code under the Apache license, a license is open standard software and mobile devices.

In this world there are two types of distributors operating system Android. The first fully supported by Google or Google Mail Services (GMS) and the second is a completely free distribution without the direct support Google's otherwise known as the Open Handset Distribution (OHD).

Content Based Image Retrieval System

Image Retrieval System at the beginning of its development which is around the late 1970s, still use text to mark or give a description (annotation) to the image. First image captioned text form and then to do the retrieval process used DBMS (Database Management System)-based text. Provision of such information has the disadvantage that is: if a collection of images has a very large number, it becomes inefficient because the process is done manually and the information provided in the image is subjective, highly dependent on the perceptions of informants. To overcome these problems, in the early 1990s began to be developed CBIR (Content-Based Image Retrieval) that perform the retrieval based on visual content (visual content). The charge distribution can be either visual color, texture or form (shape) owned the image. In general CBIR system can be expressed in the diagram in figure below

visual content of images in the database is extracted, then described as a feature vector (feature vector) and stored in the database feature. To get back an image, users give input to the system in the form of an example image to be searched, the process is called the QBE (Query By Example). The system then change the sample image into the form of characteristic vectors and compare the level of similarity (similarity comparison) with feature vectors in the feature database. In the process of comparing the similarity indices used in the feature vectors in order to access the database more efficient. Process is then performed based image retrieval and sorting the resulting value to the process of benchmarking the level of similarity. Retrieval systems today also have involved the feedback from the user whether an image retrieval results are relevant or not (relevance feedback) is used as reference to modify the retrieval process in order to obtain more accurate results.