Improving Sonar Image Patch Matching via Deep Learning

Matching sonar images with high accuracy has been a problem for a long time, as sonar images are inherently hard to model due to reflections, noise and viewpoint dependence. Autonomous Underwater Vehicles require good sonar image matching capabilities for tasks such as tracking, simultaneous localization and mapping (SLAM) and some cases of object detection/recognition. We propose the use of Convolutional Neural Networks (CNN) to learn a matching function that can be trained from labeled sonar data, after pre-processing to generate matching and non-matching pairs. In a dataset of 39K training pairs, we obtain 0.91 Area under the ROC Curve (AUC) for a CNN that outputs a binary classification matching decision, and 0.89 AUC for another CNN that outputs a matching score. In comparison, classical keypoint matching methods like SIFT, SURF, ORB and AKAZE obtain AUC 0.61 to 0.68. Alternative learning methods obtain similar results, with a Random Forest Classifier obtaining AUC 0.79, and a Support Vector Machine resulting in AUC 0.66.Comment: Author versio

Laryngoscopic Image Stitching for View Enhancement and Documentation - First Experiences

One known problem within laryngoscopy is the spatially limited view onto the hypopharynx and the larynx through the endoscope. To examine the complete larynx and hypopharynx, the laryngoscope can be rotated about its main axis, and hence the physician obtains a complete view. If such examinations are captured using endoscopic video, the examination can be reviewed in detail at a later time. Nevertheless, in order to document the examination with a single representative image, a panorama image can be computed for archiving and enhanced documentation. Twenty patients with various clinical findings were examined with a 70 rigid laryngoscope, and the video sequences were digitally stored. The image sequence for each patient was then post-processed using an image stitching tool based on SIFT features, the RANSAC approach and blending. As a result, endoscopic panorama images of the larynx and pharynx were obtained for each video sequence. The proposed approach of image stitching for laryngoscopic video sequences offers a new tool for enhanced visual examination and documentation of morphologic characteristics of the larynx and the hypopharynx

a simple robust scaleinvariant text feature detector

In this paper we present SITT, a simple robust scaleinvariant text feature detector for document mosaicing. Digital image stitching has been studied for several decades. SIFT-Features in combination with RANSAC algorithm are established to produce good panoramas. The main problem of realtime text document stitching is the size of the feature set created by SIFT-Features. We introduce SITT-Features to solve this problem. Our experiments denote that for document images SITT-Features produce faster good results than SIFT-Features

Toward the vision based supervision of microfactories through images mosaicing.

International audienceThe microfactory paradigm means the miniaturisation of manufacturing systems according to the miniaturisation of products. Some benefits are the saving of material, energy and place. A vision based solution to the problem of supervision of microfactories is proposed. It consists in synthetising a high resolution global view of the work field and real time inlay of local image in this background. The result can be used for micromanipulation monitoring, assistance to the operator, alarms and others useful informations displaying

Synthesizing a virtual imager with a large field of view and a high resolution for micromanipulation.

International audiencePhoton microscope connected with a camera is the usual imager required in micromanipulation applications. That microimager gives high resolution views, but the corresponding field of view are very narrow and do not allow the vision of the entire workfield. The classical solution consists in using multiple views imaging system: a high resolution imager for local view and a low resolution imager for global view. We are developing an alternative solution based on image mosaicing that requires only one microimager. The views from that real microimager are associated in order to achieve a virtual microimager which combines a large field of view with a high resolution

IVOA Recommendation: Simple Image Access Specification Version 1.0

This specification defines a protocol for retrieving image data from a variety of astronomical image repositories through a uniform interface. The interface is meant to be reasonably simple to implement by service providers. A query defining a rectangular region on the sky is used to query for candidate images. The service returns a list of candidate images formatted as a VOTable. For each candidate image an access reference URL may be used to retrieve the image. Images may be returned in a variety of formats including FITS and various graphics formats. Referenced images are often computed on the fly, e.g., as cutouts from larger images