IMAGEFRAMER REVIEWS OFFLINE

It can be concluded that our system reaches the benchmark moreover, in most cases our method outperforms the others, especially in the cases of queries with many objects. Our solution is compared with the famous web images search engines (Google, Bing and Flickr), and there is a comparison of their Mean Average Precision (MAP) values. Our search methods use confidence values of object classifiers and after the evaluation, the best method is selected for thorough analysis.

We have elaborated more search methods for combining the results of binary classifiers of objects in images.

IMAGEFRAMER REVIEWS OFFLINE

The results of this offline classification are stored for the latter search task. We have used the state-of-the-art image processing methods prior to the search, such as Fisher-vector and C-SVC classifier, in order to semantically classify images containing multiple objects. In this paper, we present a new semantic image search system, which is capable of multiple object retrieval using only visual content of the images. The progress of image search engines still proceeds, but there are some challenges yet in complex queries. Various pooled vectors are used to describe regions of images in event tracking, entire image descriptors for image comparison in content based image retrieval, and as region descriptors to be used in a content based image retrieval system on the SDO AIA image pipeline. We produce such descriptors by pooling sparse coding vectors produced by spanning learned basis dictionaries. To this end, we are concerned with the creation of image region descriptors that are selective enough to differentiate between highly similar images yet compact enough to be compared in an efficient manner, while also being indexable with current indexing technology. This has created a massive repository of high-quality solar images to analyze and categorize. This mission has been in operation for several years and produces almost 700 Gigabytes of data per day from the Atmospheric Imaging Assembly instrument alone. In this thesis, we focus on the task of creating a method of comparison for images produced by NASA’s Solar Dynamic Observatory mission. Comparing regions of images is a fundamental task in both similarity based object tracking as well as retrieval of images from image datasets, where an exemplar image is used as the query.

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