The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, we address the task of instance-level semantic boundary detection. To this end, we generate a large database consisting of more than 10k images (which is 20 bigger than existing edge detection databases) along with ground truth boundaries between 459 semantic classes including instances from both foreground objects and different types of background, and call it the PASCAL Boundaries...
This research aims to examine the effectiveness and efficiency of fuzzing hashing algorithm in the identification of similarities in Malware Analysis. More precisely, it will present the benefit of using fuzzy hashing algorithms, such as ssdeep, sdhash, mvHash and mrsh – v2, in identifying similarities in Malware domain. The obtained results will be compared with the traditional and most common Cryptographic...
Semantic segmentation, or segmenting all the objects in an image is one of the core problems of computer vision. In order to achieve an object-level semantic segmentation, we propose to label image regions and to improve the segmentation result based on these labels. We build upon the recent super parsing approach, which is a nonparametric solution to the image labelling problem. We propose to initialize...
The document layout analysis is a complex task in the context of heterogeneous documents. It is still a challenging problem. In this paper, we present our contribution for the layout analysis competition of the international Maurdor Campaign. Our method is based on a grammatical description of the content of elements. It consists in iteratively finding and then removing the most structuring elements...
In this paper we investigate the problem of segmenting images using the information in text annotations. In contrast to the general image understanding problem, this type of annotation guided segmentation is less ill-posed in the sense that for the output there is higher consensus among human annotations. In the paper we present a system based on a combined visual and semantic pipeline. In the visual...
Text line segmentation is one of the main parts of document image analysis, it provides crucial information for automated reading, word spotting, alignment between image and transcription, or indexing of documents. Yet it remains an open problem for handwritten historical documents because of complex layouts on the one hand, such as curved and touching text lines, and binarization problems on the...
This paper presents the implementation of an efficient retrieval system for medical images. By combining ontology with the use of low level feature extraction we were able to retrieve meaningful information from the knowledge base. We also successfully bridged the gap between the low level feature and the high level semantics by applying the image processing technique to extract the low level features...
Accurate matching of local features plays an essential role in visual object search. Instead of matching individual features separately, using the spatial context, e.g., bundling a group of co-located features into a visual phrase, has shown to enable more discriminative matching. Despite previous work, it remains a challenging problem to extract appropriate spatial context for matching. We propose...
We solve the problem of localizing and tracking household objects using a depth-camera sensor network. We design and implement Kin sight that tracks household objects indirectly -- by tracking human figures, and detecting and recognizing objects from human-object interactions. We devise two novel algorithms: (1) Depth Sweep -- that uses depth information to efficiently extract objects from an image,...
The human cortex is a folded ribbon of neurons with a high inter-individual variability. It is a challenging structure to study especially when measuring small changes resulting from normal aging and neurodegenerative disorders such as Alzheimer's Disease (AD). Recent studies have proposed surface based approaches for statistical population comparison of cortical changes since such approaches better...
This paper presents a novel learning-based method for single image super-resolution (SR). Given an input low-resolution image and its image pyramid, we propose to perform context-constrained image segmentation and construct an image segment dataset with different context categories. By learning context-specific image sparse representation, our method aims to model the relationship between the interpolated...
Conventional approaches to image annotation tackle the problem based on the low-level visual information. Considering the importance of the information on the constrained interaction among the objects in a real world scene, contextual information has been utilized to recognize scene and object categories. In this paper, we propose a Bayesian approach to region-based image annotation, which integrates...
This paper proposes a context-constrained hallucination approach for image super-resolution. Through building a training set of high-resolution/low-resolution image segment pairs, the high-resolution pixel is hallucinated from its texturally similar segments which are retrieved from the training set by texture similarity. Given the discrete hallucinated examples, a continuous energy function is designed...
Graphics detection and recognition are fundamental research problems in document image analysis and retrieval. As one of the most pervasive graphical elements in business and government documents, logos may enable immediate identification of organizational entities and serve extensively as a declaration of a document's source and ownership. In this work, we developed an automatic logo-based document...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.