Commissariat a L'energie Atomique

Adermip (association Pour Le Development De L'enseignement De L'economic

Didier Juvin

Hassane Es-Safi

Benoit Dupeyrat

Shenbiao Tan

Jean-Luc Basille

Jean-Yves Latil

The present invention concerns a data-processing device relating to pixels. This data is marked per line and per column. The device comprises processing means comprising at least four identical processors, (PE0, PE1, PE2, PE3) respectively connected to memories (MEM0, MEM1, MEM2, MEM3) marked on row J=0 to row J=3. The data relating to the pixels to be processed are recorded in the memories according to an helicoidal addressing. Connection means (1C0, 1C1, . . . , 2C0, 2CE1, . . . ) are provided so that the processors are connected according to a looped line configuration.

Data processing device with processors arranged in a looped line

The invention relates to a process for the recognition of objects liable to overlap, on the basis of reference images of said objects and the image of the group of said objects. The process consists of coding successive elementary segments, whose ends are substantially located on the contour of each image in the 'learning' phase of the contour of each object and in the object recognition phase. Pairs of characteristic segments in the contour of each image are then investigated, each characteristic segment being oriented and defined by its oriented angle, its length and its origin. Each pair giving a good image discrimination is called a transition vector. These vectors are hierarchized for the reference images and compared with the transition vectors of the image of the objects to be recognized. For any object assumed to be recognized, a fine verification takes place on the elementary segments. Application to the recognition or identification of objects and to artificial vision in robotics.

Process for the automatic recognition of objects liable to overlap

A process for the automatic recognition of an image (I) on the basis of a corresponding reference image, including obtaining, by optoelectronic detection means (C), signals representing both the image to be recognized and the reference image, digitizing (in CAN) and recording the respective signals in a memory (M), using a processing unit (UT) to determine the coordinates of respective characteristic contour lines in the image to be recognized and the reference image, segmenting the respective contour lines and coding the segments (Si), attributing to each segment a pair of values (.rho..sub.i, .theta..sub.i) relating to its length (.rho..sub.i) and its angle (.theta..sub.i) compared with a reference direction, and comparing the respective pairs of values while seeking coincidence between the large segments of the contour to be recognized and the reference contour. The process has application to the recognition of shapes, particularly in robotics.

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Didier Juvin