Time filter

Source Type

Dubrovina A.,Computer Science | Kisilev P.,IBM | Freedman D.,IBM | Schein S.,HP Labs Israel | Bergman R.,HP Labs Israel
Proceedings - International Conference on Pattern Recognition | Year: 2012

Graphical User Interface (GUI) object classification is essential for image-based software automation tools. The challenges posed by GUI object classification are significantly different from those in natural image classification. In this paper we present a novel image descriptor developed specifically for GUI objects; it is robust to various changes in the appearance of GUI objects, such as various screen resolution, 'skin', as well as various operating system related. We use this image descriptor with Support Vector Machine classifier, and experimentally show the descriptor robustness to the above transformations, and its superior performance compared to existing image descriptors. © 2012 ICPR Org Committee.

Barkol O.,HP Labs Israel | Bergman R.,HP Labs Israel | Kasravi K.,Hewlett - Packard | Golan S.,HP Labs Israel | Risov M.,Hewlett - Packard
HP Laboratories Technical Report | Year: 2012

We describe an application for rapidly and optimally responding to enterprise opportunities and challenges, by leveraging the tacit knowledge in an enterprise, via identifying the right subject matter expert(s). Enterprise Collective is a web application that automatically discovers experts and their expertise via semantic analysis of their work products (e.g., e-mails, patents, papers, reports, presentations, and blogs). The key feature of Enterprise Collective is being "passive"; where the employees do not fill out or maintain forms or profiles. The application provides an interactive user interface that hides the underlying complexity. Enterprise Collective can benefit any business user, without extensive training or any analytical background. The application leverages the Expert-Expertise, Expert-Documents, and Expertise-Documents relationships, and subsequently permits navigation within this knowledge space. Enterprise Collective uses technologies for semantic analysis of work products and relevance computation using graph flow. A semi-automatic taxonomy generator is used to extract expertise from documents. The "authority" of each expert in relation to an expertise is computed via the nature of the work product and frequency of references. To demonstrate the benefit of Enterprise Collective in large organization, we describe a case study. © Copyright 2012 Hewlett-Packard Development Company, L.P.

Tadeski I.,HP Labs Israel | Barkol O.,HP Labs Israel | Bergman R.,HP Labs Israel
HP Laboratories Technical Report | Year: 2012

We suggest a method to automatically evaluate employees' subject matter expertise in knowledge management systems. The approach stems from several conclusions that arose in extensive research of subject matter experts and their expertise. We find that self-reported expertise is biased and constantly changing. We, furthermore, observe that automatic methods to infer expertise perform about as well as self-reported profiles. The crux of the proposed method is to combine automatic inference expertise with the benefit of the expert's opinion, and to do so periodically so the profile remains accurate and fresh. © Copyright 2012 Hewlett-Packard Development Company, L.P.

Nachlieli H.,Hp Labs Israel | Karni Z.,Hp Labs Israel | Raz S.,HP Indigo
International Conference on Digital Printing Technologies | Year: 2011

We present an expert system for identifying print artifacts. The system balances between subjective sensitivities of print quality with an evaluation of the objective machine state (which may result in visible print artifacts). For example, fine bands may appear due to the mis-calibration of one machine component, while low contrast stains may exist on the same printing due to the state of another component. Different markets have different needs and hence may have different sensitivities to the same two artifacts: Marketing collateral customers may be more sensitive to the low contrast stains and less to the fine bands. On the other hand, photo album's customers may be more sensitive to the fine bands, and Direct Mail customers may accept the printing as valid. To achieve this balance, we combine an interactive expert system with an automatic analysis of dedicated print jobs. The expert system guides the user in classifying the print artifact according to his subjective sensitivities. Utilizing an inline-scanner enables automatic procedures for the detection of artifacts caused by an objective machine state. Benefits of the system include better control of print quality and better use of consumables. ©2011 Society for Imaging Science and Technology.

Karni Z.,Hp Labs Israel | Gaash A.,HP Indigo
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2012

We present an algorithm for smart image fitting: changing the size of an image so that it may fit "naturally" within a given frame. As the frame's dimensions will generally differ from that of the image, the algorithm preserves important details in their original aspect ratio, while less important details undergo more substantial deformations. This problem is useful for many commercial print applications. One example is the HP SmartStream Designer, which is a tool to create variable and personalized content documents. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Shapira L.,Hp Labs Israel | Staelin C.,Hp Labs Israel | Banner R.,Hp Labs Israel
International Conference on Digital Printing Technologies | Year: 2011

We propose a method to maintain image sharpness consistency across different devices, analogous to the way ICC profiles are used to maintain color consistency. The method is based on creating a profile of the perceived blur caused by the printing and viewing process. We show how to measure and analyze the sharpness profile of a printer, and demonstrate that the profile consists of multiple 2D modulation transfer functions (MTF's), varying over different ink combinations and colors. We propose storing the sharpness profile within an ICC profile. The profile can then be used to adaptively pre-compensate for the induced blur, and maintain sharpness consistency. ©2011 Society for Imaging Science and Technology.

Loading HP Labs Israel collaborators
Loading HP Labs Israel collaborators