Access to collections of cultural heritage is increasingly becoming a topic of interest for institutions like libraries. With the easy access to information provided by technologies such as the Internet, new ways exist for consulting ancient documents without exposing them to more dangers of degradation. One of those types of documents is written ancient music. These documents suffer from multiple kinds of degradation, where bleed-through outstands as the most damaging. This paper proposes a new method based on the Takagi Sugeno fuzzy classification algorithm to classify the pixels as bleed-through, after performing a general background restoration. This method is applied to a set of doublesided ancient music documents, and the obtained results compared with methods present in the literature.
A new uncalibrated eye-to-hand visual servoing based on inverse fuzzy modeling is proposed in this paper. In classical visual servoing, the Jacobian plays a decisive role in the convergence of the controller, as its analytical model depends on the selected image features. This Jacobian must also be inverted online. Fuzzy modeling is applied to obtain an inverse model of the mapping between image feature variations and joint velocities. This approach is independent from the robot's kinematic model or camera calibration and also avoids the necessity of inverting the Jacobian online. An inverse model is identified for the robot workspace, using measurement data of a robotic manipulator. This inverse model is directly used as a controller. The inverse fuzzy control scheme is applied to a robotic manipulator performing visual servoing for random positioning in the robot workspace. The obtained experimental results show the effectiveness of the proposed control scheme. The fuzzy controller can position the robotic manipulator at any point in the workspace with better accuracy than the classic visual servoing approach.
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