Alain Mérigot

Parallel asynchronous computations for image analysis

Many works have been done for parallelizing low-level image analysis computations. However the task is harder for higher levels, as the data manipulations are complex, and there is a wide range of algorithms to encompass. To allow concurrently speed and programmability, a high-level programming model that can be efficiently implemented on parallel architectures is required. To achieve this goal, we propose the associative nets model, a parallel computing model for image analysis based on simple data-parallelism paradigms, providing special features, such as graph-based data structures to handle irregular data, virtual data-structures to ease hierarchical image descriptions, and specific primitives (dirassoc) to compute on the interpixels relation graph. For implementation purposes, the dirassoc computing primitive performs asynchronous local computations until it reaches stability. Asynchronism has many advantages for hardware (speed, power consumptions, and chip size) as well as in software (less synchronization barriers). However to insure completion of the asynchronous operation, the dirassoc must use a set of specific operators (r-operators) introduced by Ducourthial. In this paper we emphasize on the interest of the r-operators and of the asynchronous computations for image analysis algorithms. We give applications in distance transforms, contour closing, Voronoi segmentation, watershed segmentation, and mathematical morphology. Hence, we show that asynchronous computations are powerful tools for image analysis on interpixel graphs.

Video-rate image segmentation by means of region splitting and merging

This paper proposes a fast method for image segmentation. After an optimal split of the image into rectangular regions, this paper focuses on the fast merging of these regions. Since the computation time is very small, hence it is suitable for real time applications, while producing a good segmentation for tracking purposes.

Connected component support for image analysis programs

This paper presents a new scheme for software support of image analysis. It extends the data parallel programming model with the notion of connected component. Thanks to a graph based model, called associative nets, connected component manipulations can be expressed in terms global object-based transformations. This model has been embedded in the Pacco interactive image analysis environment and allows flexible handling of regions and contours, as illustrated by a set of examples.

Revisiting image splitting

The paper presents a modified version of the classical split and merge algorithm (Horowitz, S. and Pavlidis, T., 1976). Instead of performing a regular decomposition of the image, it relies on a split at an optimal position that makes a good interregion separation. The implementation of the algorithm uses an initial image preprocessing to speed-up computation. Experimental results show that the number of regions generated by the split phase is largely reduced and that the distortion of the segmented image is smaller, while the execution time is slightly increased.

A massively parallel implementation of fractal image compression

The recent application of fractal techniques is a significant development in image compression. These fractal methods provide very high compression ratios for natural scenes. Fractal methods have the advantage of being resolution independent. However, their encoding complexity is O(n/sup 4/) for an n/spl times/n pixel image. This prohibits their real-time application. We propose a massively parallel implementation on a pyramid machine that yields a considerable speedup. This implementation reduces the fractal encoding complexity to O(n/sup 2/). Our parallel method has much better performance than other existing methods.<<ETX>>

Anet: a programming environment for parallel image analysis

In this paper we present the programming environment Anet for image analysis, that aims to bridge the gap between programmability requirements and parallel efficiency. It is based on the graph based associative nets computing model, and allows irregular data manipulation. As it is intrinsically a parallel model, parallel execution can be quite naturally considered, and as the number of primitives is small, effective parallelization requires an initial limited effort and can be reused by a large set of programs.

Voting spaces cooperation for 3D plane detection from monocular image sequences

This paper deals with 3D scene reconstruction from an on-board moving camera in the context of automatic driver assistance systems. The aim of our study is to detect any kind of parameterized surface from a moving camera without camera calibration or any prior knowledge about the vehicle egomotion. We assume that the 3D scene is a set of 3D planes that are classified into three categories according to their orientation: lateral planes (buildings), horizontal planes (the road) and frontal planes (moving cars or crossing pedestrians). We propose an iterative voting process that takes advantages of some specific iso-velocity curves properties in order to build a set of appropriate voting spaces. Each of them facilitates the detection of a specific plane model. A tough problem as the detection of a parameterized surface from a moving camera is reduced to an easy maxima finding in several voting spaces. We focus in this paper on the iterative scheme that allows to deal with several spaces at the same time. We choose to adapt an histogram splitting approach in order to achieve a complete plane detection process.

A communication mechanism and its implementation in the Multi-SIMD massively parallel machine SPHINX

Abstract This paper presents the communication mechanism for Multi-SIMD parallel computer SPHINX implemented as a set of MIMD machines. The described mechanism subdivides the controller of each SIMD machine in two levels, spliting thus the problems of accesses to the data and the management of communications. Communication mechanism includes synchronization functions. It uses floating channel objects implemented in the shared memory. The exclusive access to communication channels uses simple hardware mechanism based on a clock of the system, and does not require the multi-port memory.

Model-based optical flow for large displacements and homogeneous regions

Monocular motion analysis for advanced driver assistance systems (ADAS) is a very active research topic. However, two constraints limit the implementation of existent techniques in autonomous vehicles: poorly textured regions and large displacements due to vehicle egomotion that both lead to matching ambiguities. Coarse-to-fine strategies are generally used to deal with large motion, but the lack of large texture makes this approach inefficient to estimate road relative displacement. In this paper, we propose to assist the optical flow process by exploiting both a 3D scene model and a rough velocity estimate from either other embedded sensors or egomotion estimations from the previous frames. Using the available a priori knowledge allows to compensate the dominant flow to facilitate the estimation of the remaining part by a classical optical flow method. We give results on both synthetic and real image sequences and compare our approach to other existing methods.

Parallelizing image analysis algorithms: ANET solution and performances

Several hard problems have to be addressed in order to parallelize image analysis algorithms. Indeed, at the region level, these algorithms handle irregular (and sometimes strongly dynamic) data-structures. Moreover, they often lead to an unbalanced amount of computations, which is quite impossible to foresee offline. This paper focus on the parallelization of the ANET image analysis programming environment. Thanks to graph related data structures and efficient computing primitives, ANET allows rapid image algorithm prototyping. But in return, these primitives are difficult to parallelize. We present a solution for powerful implicit parallelization of the ANET environment, without any change in the application programming interface. The ANET API is summarized and illustrated with some examples. Several parallelization experimentations are reported. The solution we propose is detailed, and results are given on complete image analysis applications. ANET appears as a powerful environment, both for its expressiveness that allows rapid prototyping and for its implicit parallelization that allows good computation time.