Computer vision systems are frequently used for inspection and classification of products during manufacturing. Image processing and analysis allows non-invasive extraction of object features within an image and the classification of objects based on the extracted data. Shape, texture and color are typical features that can be extracted from an image and used for object recognition. In this paper, a method of detection, segmentation and classification of resistors captured in digital image, based on their nominal values, is presented. The process consists of the following steps: image segmentation, morphological image processing, representation and description of objects, object features extraction, classification of extracted data using support vector machines (SVM). Experimental results show that the proposed method exhibits solid performance and real-time operating capabilities.

This paper presents the work in progress on the design and testing of a distributed ultrasound-based sensory system for hybrid 1D and 2D environment visualisation. Many common sensors used in robotics, such as infrared and ultrasonic sensors, cameras and lasers mainly focus on quantifying distances and shapes, while rarely have the ability to differentiate among different sensed surfaces/materials. We propose an inexpensive prototype sensory system based on popular ultrasonic sensors which uses ultrasonic reflections to determine the acoustic reflection coefficients. This additional feature allows differentiating among sensed objects. Moreover, the developed ultrasonic cells are equipped with a microcontroller for basic signal processing and a communication link for integration into a sensor network. In this paper, we discuss the possibility of fusing obtained sensor array data and laser measurements.

Objective: This study was aimed to investigate the reliability of a computer application for assessment of the stages of cervical vertebra maturation in order to determine the stage of skeletal maturity. Material and methods: For this study, digital lateral cephalograms of 99 subjects (52 females and 47 males) were examined. The following selection criteria were used during the sample composition: age between 9 and 16 years, absence of anomalies of the vertebrae, good general health, no history of trauma at the cervical region. Subjects with lateral cephalograms of low quality were excluded from the study. For the purpose of this study a computer application Cephalometar HF V1 was developed. This application was used to mark the contours of the second, third and fourth cervical vertebrae on the digital lateral cephalograms, which enabled a computer to determine the stage of cervical vertebral maturation. The assessment of the stages of cervical vertebral maturation was carried out by an experienced orthodontist. The assessment was conducted according to the principles of the method proposed by authors Hassel and Farman. The degree of the agreement between the computer application and the researcher was analyzed using by statistical Cohen Kappa test. Results: The results of this study showed the agreement between the computer assessment and the researcher assessment of the cervical vertebral maturation stages, where the value of the Cohen Kappa coefficient was 0.985. Conclusion: The computer application Cephalometar HF V1 proved to be a reliable method for assessing the stages of cervical vertebral maturation. This program could help the orthodontists to identify the stage of cervical vertebral maturation when planning the orthodontic treatment for the patients with skeletal disharmonies.