**1. Introduction**

In the last decade, the possibilities of autonomous decision making by computer vision systems have been actively studied. The topic of autonomous agents to support solutions that are able to adapt to the environment is relevant in a variety of applications: medicine [1–3], systems and means of artificial intelligence [4–6]. The problem includes the question of where fuzzy logic is needed [7], security issues [8–11] and biometric recognition systems [12,13], systems to support people with disabilities and related technologies and applications aimed to include wayfinding and navigation [5,13], land research, space research, agricultural issues, industrial climate issues, smart things, etc.

The task of automated selection of key characteristics for the classification of images using computer tools is not a trivial problem [14–16]; especially for the variable field of attention [17,18]. There are many methods and algorithms for identifying key characteristics for image classification [19–24], but each has its disadvantages and advantages. Most of the existing methods that solve this problem are effective only for individual objects, such as human faces, simple geometric shapes, and handwritten or printed symbols, but only under certain conditions, including certain lighting and the position of the object from the wearable camera and background. An urgen<sup>t</sup> problem now is the creation of automated systems that compensate for the limited capabilities of people at different levels. When using artificial neural networks [19,20], reducing the amount of computation in learning is an important element to teach mathematical options for processing. This paper considers the problem of comparing the methods of selection of characteristic features under different external conditions in order to identify the best method for given conditions. Adaptive algorithms for detecting, classifying, and tracking the edges of objects have been developed

**Citation:** Hrytsyk, V.; Medykovskyy, M.; Nazarkevych, M. Estimation of Symmetry in the Recognition System with Adaptive Application of Filters. *Symmetry* **2022**, *14*, 903. https:// doi.org/10.3390/sym14050903

Academic Editors: Peng-Yeng Yin, Ray-I Chang, Youcef Gheraibia, Ming-Chin Chuang, Hua-Yi Lin and Jen-Chun Lee

Received: 16 February 2022 Accepted: 28 March 2022 Published: 28 April 2022

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in [25]. Adaptation is achieved by using thresholds to obtain contours. The creation of contours is achieved through the Kalman filter, the use of which significantly improves the computation time, as well as provides the system with the required accuracy. In [26], invariant approaches to structural features were used to find facial features, texture, shape, and color of the skin regardless of changes in lighting. Statistical models have been developed, which are the basis for testing the model. The advantage of the proposed method is that it can detect faces of different sizes and different poses without restrictions on lighting conditions. However, the spectral characteristics of the face / skin are not studied in this work. In [27], for an image that is under background and lighting conditions, a method for determining the edges based on the advanced arithmetic operator Prewitt was proposed. An improved preprocessing operation was performed in the work. The characteristics of horizontal projection and vertical location of the upper and lower edges for positioning were used. The results of the experiments show that the algorithm has high speed, positioning speed, and good practical value.

Table 1 shows the increase in absolute contrast values from the state of the object. The state of the object can change tens of thousands of times, and up to one million times when exposed to the sun. Because glare affects the brightness of an object, the brightness of the sun's disk can reach up to 108 lux. Shade illumination can be reduced to 100 lux. Today, it is impossible to observe several objects with tens of thousands of different illuminations on the same camera. Therefore, the inevitable loss of information.


**Table 1.** Lighting on the object in the Suites.

The aim of the work is to create adaptive systems of perception in the visible spectrum by constructing the dependences of the quality of the applied filters in dynamically changing conditions. In particular, the paper studies the behavior (in terms of symmetry of object representation) of the most popular methods of detecting edges under different lighting conditions.

#### **2. Materials and Methods**
