Research Article | Open Access | Download PDF
Volume 67 | Issue 6 | Year 2019 | Article Id. IJETT-V67I6P220 | DOI : https://doi.org/10.14445/22315381/IJETT-V67I6P220
Flexible Burst Image Capture System for Mobile Devices
Akul Taneja, Megha Gupta, Ronak Goel, Vobbilisetty Sushant
Citation :
Akul Taneja, Megha Gupta, Ronak Goel, Vobbilisetty Sushant, "Flexible Burst Image Capture System for Mobile Devices," International Journal of Engineering Trends and Technology (IJETT), vol. 67, no. 6, pp. 106-110, 2019. Crossref, https://doi.org/10.14445/22315381/IJETT-V67I6P220
Abstract
In this paper a newfangled selective image capturing approach is described where all events of the current scenario are intended to be captured. Mobile phone usage has seen an exponential increase in the last few years and hence mobile phone photography has progressed rapidly. Phone camera is your best camera, because it is always with you. Our photographic brains are switched on all the time, looking for possibilities to capture the expected and unexpected moments. There are numerous scenarios where a user might want to capture images without missing any event, which is tedious if manual clicking is adopted. To capture continuous shots burst mode is devised, but it has fixed rate of image capture and results in many similar and unnecessary images even if there is no significant change in the scenario. Towards such needs, it is quite necessary to develop an intelligent system that captures image only when a new information is added to the scenario, hence saving memory, enhancing battery life and thereby improving the overall device performance without restricting the user needs. A software based solution has been developed in this research that performs selective capture without human interaction by continuously varying rate of image capture by dissecting the scenario, identifying constituents and their characteristics, applying movement restrictions and identifying disruption parameters. In this way, it is ensured that all the useful information, which user wants from a scenario, is successfully captured. The proposed mechanism is called as Flexible Burst Image Capture System for Mobile Devices. It has three inter-dependent modules (1) Context Detection & Object Classification module (2) Object Tracking & Scene Change Detection module (3) Scene Change Estimation module. Content Detection and Object Classification module is responsible for identification of different objects/backgrounds entering and exiting the scene. Once the object/background is successfully identified, it classifies them further according to their type. Object Tracking and Scene Change Detection module monitors the identified objects/background by the first module. Scene Change Estimation module, takes continuous input from the first two modules to devise the new image capture rate so that only images representing some new and important information are captured, without any duplication. In this way this mechanism helps user to capture all important moments without compromising on storage space.
Keywords
Image capture, Storage space, Context Detection, Object Classification, Object Tracking, Scene Change Detection, and Scene Change Estimation.
References
[1] J. M. Bioucas-Dias and G. Valadao. Phase unwrapping via ˜ graph cuts. IEEE Trans. on Image Processing, 16(3):698– 709, 2007
[2] G. W. Larson, H. Rushmeier, and C. Piatko. A visibility matching tone reproduction operator for high dynamic range scenes. IEEE Trans. on Visualization and Computer Graphics, 3(4):291–306, 1997
[3] O. Gallo, N. Gelfand, W.-C. Chen, M. Tico, and K. Pulli. Artifact-free high dynamic range imaging. In Proc. of International Conference on Computational Photography (ICCP), 2009