The descriptive model of perception of image form
Rimantas Grikšas
Published 2005-01-01


image form

How to Cite

Grikšas R. (2005). The descriptive model of perception of image form. Psichologija, 31, 113-123.


There is a descriptive model of form perception being analyzed in the article, and there has been used a small number of invariant samples for it. These are the samples that would not depend on various image transformations.
The data for analysis has been received through tests and analysis of works of imitative arts after there had been an assumption made that imitative arts reflect the system of form perception. It means that the artist expresses the form of thing in already simplified proportions of dimensions. The article analyzes just the perception of form of the objects that are in the frontal projection, or that are plane.
There was one of the features analyzed – orientation of outline fragments and their situation in the space. There were ignored such factors as texture, color of object, etc. Besides, while making the model of image formation, we have ignored such an effect of normalization, where the orientation of the object in space is corrected with respect to vertical and horizontal axes.
In the perception system that is analyzed in the article the form of the thing is perceived (determined) by the comparison of particular parameters. There have been excluded three main ways of determination: 1) determination of angular values; 2) determination of linear values (distances); 3) determination of curves. In all the cases separate parameters are compared with a module. The determination module of angular values is angle of 90° (right) and its multiples, i.e. angles of 180°, 270° and 360°. In other cases the module is the biggest value of object’s gabarit that is parallel to the symmetric axis. The parameter is determined (perceived) as the ratio of value and module. The main module of the object plays a crucial role in excluding the object from environment.
The recognition process consists of fragmentation of figure (separation to single parts), while the figure is defined by the set of fundamental elements. However, the question remains how to perform fragmentation and to join separate fragments into one set that makes the object. If the fragmentation is performed by attributing separate lines (parameters) to some adequation type, then the crucial role in fragmentjoining to one-piece object is played by main linear module. The exclusion of main module and its usage in the proportions while perceiving the image are the items that allow seeing the object as one set.
The values of determined proportions are round down the close ratios of small whole numbers. In such a way the amount of processed information is diminished as well. Thus when the form of the object is perceived, any parameter is perceived as its closest parameter that forms a ration with main module, which is expressed in the smallest possible nature numbers.
The model of form perception that is introduced in the article is close to the structuralism – one of the oldest hypotheses of perception. The main drawback of this system is the usage of big amount of the elements that form an image. The elements that form an image are the regular geometrical figures. These are traditional figures: spheres, cylinders, cones. When their image is being made their form cannot change a lot. Only the general size and proportions of gabarits may change. The authors describe these figures in purely mathematical algorithms that do not have any connection to the image. Therefore it is difficult to assemble various forms from these figures. Besides, a big number of variants of elements is needed for such a purpose.
The elements that are presented in the article as the ones that form an image are dynamic figures made from the types of differently determined lines. The values that describe the figures are the parameters that are clearly perceived in the image. Moreover, main module – a parameter that integrates the object’s image – is used in the adequation of parameters. It allows describing any form of especially small amount of samples. 


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