Process for the automatic recognition of objects liable to overlap

• US 4,845,765 A
• Filed: 06/08/1988
• Issued: 07/04/1989
• Est. Priority Date: 04/18/1986
• Status: Expired due to Fees

• Current Assignee: Commissariat a L'Energie Atomique (French Alternative Energies and Atomic Energy Commission)
• Original Assignee: Commissariat a L'Energie Atomique (French Alternative Energies and Atomic Energy Commission)
• Inventors: Tan, Shenbiao, Juvin, Didier
• Primary Examiner(s): Boudreau, Leo H.
• Assistant Examiner(s): NOT, DEFINED
• Application Number:
  US07/207,000
• Time in Patent Office: 391 Days
• Field of Search: 382/8, 382/21, 382/22, 382/25, 382/60, 382/15, 382/37
• US Class Current: 382/153
• CPC Class Codes: G06V 10/469 Contour-based spatial representations, e.g. vector-coding

Abstract

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.

Claims

1. Process for the automatic recognition of objects liable to overlap, on the basis of respective reference images of said objects, and the image of a group of objects to be recognized, said images being stored in the form of digital values representing for each image the coordinates of the points of a contour line of said image, in a frame of reference, said process consisting of coding for each image, successive elementary segments, the ends of each elementary segment being substantially located on the same contour line, so that for each segment, said coding gives the length of said segment, as well as its angle with respect to a reference direction, said coding operation being performed both during a "learning" phase of the different objects to be subsequently recognized and in a subsequent "recognition" phase of the objects liable to overlap, wherein said process comprises in the learning phase the following steps:

investigating for each reference image contour, pairs of successive or non-successive characteristic segments of said contour line, each formed from one or more elementary segments, said characteristic segments being oriented in a predetermined direction of the contour line, each pair determining a characteristic transition vector defined by parameters which include the value of an angle, oriented in the direction of the contour line, this angle being defined as the angle between the two oriented characteristic segments of the pair, the coordinates of the origin and the length of each characteristic segment of the pair, a transition vector being characteristic when its parameters provide a substantive discrimination of the contour of the corresponding object, even when said object is overlapped by one or more other objects, the parameters of the transition vectors being stored, hierarchizing the transition vectors of a contour as a function of their discrimination parameters, modifying said hierarchization of the transition vectors during the acquisition of the transition vectors of the contours of the different objects, so as to eliminate similar transition vectors for different contours, and said process comprising in the recognition phase the following steps;

performing the same transition vector determination operation in the characteristic segments of the contour of the image of the objects to be recognized, comparing in the hierarchization order, the values of the parameters of the transition vectors of the contour of the image of the objects to be recognized and the contour of the reference images of each object, so as to investigate the similarities of the values of said parameters, forming a presence hypothesis of an object corresponding to a transition vector for which the comparison has established a similarity, and effecting a fine check of said hypothesis by comparing successive elementary segments of the contour of the reference image of said object with successive elementary segments of the contour of the image of the objects to be recognized.

2. The process according to claim 1, wherein the successive elementary coded segments are obtained by Freeman coding making it possible to obtain successive segments defined by their orientations and having ends which are located on the contour line of each image, said Freeman coding being followed by a corrective processing making it possible to deduce on the basis of each Freeman-coded segment, one or more successive elementary segments, the ends of each located on the contour line of the image, said successive elementary segments being isotropic and of the same length.

3. The process according to claim 2, wherein the corrective processing consists, for each Freeman-coded segment, of differentiating said segment with respect to its order number in the contour, in order to compensate for orientation irregularities, performing a conversion of the values resulting from the differentiation of each segment in order to compensate for length irregularities, filtering the signal resulting from said conversion, sampling said signal at a constant frequency and then integrating the sampled signal, said integration producing said successive elementary coded segments, the preceding corrective processing also making it possible to extract the angular points, and consequently the characteristic segments.