Education in children is a very important part of life to achieve success in the future. Early on, children must be taught knowledge, especially related to the daily environment, including: introduction of animals. Among the characteristics of children's learning is interesting. So far, conventional learning in the form of books makes children bored, so it takes creativity or interactive learning methods, one of which is multimedia-based learning. One of the multimedia technology developed at this time is augmented reality. Mobile augmented reality based applications can be used as learning media for animal recognition for children. This interactive learning media based on Mobile Augmented Reality, called ARnimal, combines picture books and augmented reality applications. The markers contained in the picture book will be captured by the camera from the mobile device and then processed and appear animated 3D animals on the screen in realtime. By combining the real and virtual world, ARnimal can stimulate the imagination of children so that children are more enthusiastic in learning. The results of this ARnimal trial on several types of smartphones show that all ARnimal functions are running well. ARnimal was also tested on some children who were accompanied by their parents and the results of the questionnaire showed that the application was easy to use, helped with education, had similarities with real animals and had an attractive appearance.

Painting is one of complex image reflecting observations and feelings of the artist to the environment. This condition extends the need of painting impression generation system since common people with lack of art experience would have difficulties to interpret the painting. From this point of view we presents a new model to provide representative impressions of paintings by providing a color-impression metric taken from public survey and implement it for mobile application. The new model provides analytical functions to generate the representative impression of the image query. The functions consist of two main section: (1) The cultural-dependent color-impression metric creation which consist of conducting survey, applying normalized 3D color vector quantization to image dataset, generating image-impression metric, and generating colorimpression metric; and (2) Impression generation of image query which consist of applying normalized 3D color vector quantization to image query and measuring the similarity between image query and color-impression metric. To perform our proposed impression generation system, we examine our system with Indonesian cultural image dataset and 5 different mobile devices. Our proposed system performs main color impression precision result with average precision of more than 60%. Brightness intensity and zooming affects the retrieved impressions. Rotating captures of an image generate the same retrieved impressions. The system also performs average response time vary in range 41263 to 117434 milliseconds from all devices.

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