Luis Salgado

Efficient image stabilization and automatic target detection in aerial FLIR sequences

This paper presents a system which automatically detects moving targets contained in aerial sequences of FLIR images under heavy cluttered conditions. In these situations, the detection of moving targets is generally carried out through the implementation of segmentation and tracking techniques based on the images correlation maintained by the static camera hypothesis. However, detection procedures cannot rely on this correlation when the camera is airborne and, therefore, image stabilization techniques are usually introduced previously to the detection process. Nevertheless, the use of stabilization algorithms has been often applied to terrestrial sequences and assuming a high computational cost. To overcome these limitations, we propose an innovative and efficient strategy, with a block-based estimation and an affine transformation, operating on a multi-resolution approach for recovering from the ego-motion. Next, once the images have been compensated on the highest resolution image and refined to avoid distortions produced in the sampling process, a dynamic differences-based segmentation followed by a morphological filtering strategy is applied. The novelty of our strategy relies on the relaxation of the pre-assumed hypothesis and, hence, on the enhancement of its applicability, and also by further reducing its computational cost, thanks to the application of a multi-resolution algorithm. The experiments performed have obtained excellent results and, although the complexity of the system arises, the application of the multi-resolution approach has proved to dramatically reduce the global computational cost.

Automatic aerial target detection and tracking system in airborne FLIR images based on efficient target trajectory filtering

Common strategies for detection and tracking of aerial moving targets in airborne Forward-Looking Infrared (FLIR) images offer accurate results in images composed by a non-textured sky. However, when cloud and earth regions appear in the image sequence, those strategies result in an over-detection that increases very signficantly the false alarm rate. Besides, the airborne camera induces a global motion in the image sequence that complicates even more detection and tracking tasks. In this work, an automatic detection and tracking system with an innovative and efficient target trajectory filtering is presented. It robustly compensates the global motion to accurately detect and track potential aerial targets. Their trajectories are analyzed by a curve fitting technique to reliably validate real targets. This strategy allows to filter false targets with stationary or erratic trajectories. The proposed system makes special emphasis in the use of low complexity video analysis techniques to achieve real-time operation. Experimental results using real FLIR sequences show a dramatic reduction of the false alarm rate, while maintaining the detection rate.

Contourless region-based video coding for very low bit-rates

In spite of their advantages, region-based approaches present a heavy burden in the required amount of information to describe region contours. To avoid these limitations, a new region-based motion estimation and compensation strategy is proposed, which allows the operation on arbitrary shaped regions and the ability to reconstruct them without any contour information. The strategy is enhanced by the use of multivector motion estimation and compensation. Results showing the quality and advantages of the strategy are provided.

Adaptive segmentation for gymnastic exercises based on change detection over multiresolution combined differences

A new adaptive segmentation strategy is proposed to segment gymnasts in sport sequences accurately. It is based on a Markov random fields (MRF) change detection analysis operating on a multiresolution combination of static and dynamic image differences. After a morphological analysis of the segmented masks, estimated motion information in the area of interest is incorporated to improve the efficiency of the segmentation process. Although presented in the particular context of gymnastic exercises, the new segmentation strategy could be applied to other applications where moving objects on a quasi-static background need to be segmented.

Efficient prediction error regions determination for region-based video coding through shape adaptive DCT

An efficient strategy to determine the prediction error regions to be coded within a region-based prediction error coding scheme is presented. Prediction error coding is based on the segmentation of the displaced field difference (DFD) and coding the resulting arbitrary shaped DFD regions using shape adaptive DCT. Efficiency in the determination of the DFD regions to be coded is achieved by eliminating from the selection process the direct computation of the cost of region contours and textures coding. With this scheme, perceptual distortion of the decoded images is reduced while quality is locally improved on relevant image areas. Comparative results with the complete H.263 coder are shown.

Adaptive morphological time stamp segmentation based on efficient global motion estimation

An efficient segmentation technique of regular shaped sudden temporal intensity changes in image sequences is presented. It is based on morphological analysis of binarized difference images, and its parameters are dynamically modified according to an efficient estimation of the global motion of the scene. Motion analysis is carried out with the combination of a multiresolution flow estimation technique and a closed formula over the resulting motion vectors based on a simplified motion model. Specially suited for applications demanding a temporal reference, the new segmentation technique will be described in the context of a time stamp detection application.

Automatic antibiograms inhibition halo determination through texture and directional filtering analysis

A new segmentation and analysis strategy to automatically measure the inhibition halos (IHs) in antibiograms is presented. It is based on the application of a combined texture and directional filtering analysis technique on the result of a segmentation process which incorporates colour analysis and Hough transform applications. The computational efficiency is highly improved by applying the different processing stages to selected areas of the acquired images and exploiting a priori information about the IHs shape and distribution.

Multiresolution image segmentation for region-based motion estimation and compensation

An intra-frame segmentation strategy to assist region-based motion estimation and compensation is presented. It is based on the multiresolution application of a histogram clustering and a probabilistic relaxation labelling algorithm, followed by a focal gradient-based bottom-up merging procedure. Specially suited for region-based video coding, it strongly differs from other proposals in that it generates arbitrary shaped image regions with pixel accuracy at a low computational cost, while allowing full reconstruction of the segmentation at the decoder without the transmission of any region description information.

Determination of control point sets for motion description based on motion interpolation accuracy constraints

A region-based control point determination strategy for multivector motion description is proposed, which is strictly based on region contour information and the application of motion interpolation accuracy constraints to drive the location procedure. This approach gives two main advantages while keeping a reasonable computational cost: operation on arbitrary shaped regions of the image and the complete elimination of the transmission of any information related to the number and position of the control points.