Dmitriy Dubovitskiy | De Montfort University (original) (raw)

Papers by Dmitriy Dubovitskiy

Proceedings of the International Conference on Biomedical Electronics and Devices

Robotic systems and autonomous decision making systems are increasingly becoming a significant pa... more Robotic systems and autonomous decision making systems are increasingly becoming a significant part of our everyday routines. Object recognition is an area of computer science in which automated algorithms work behind a graphical user interface or similar vehicle for interaction with users or some other feature of the external world. From a user perspective this interaction with the underlying algorithm may not be immediately apparent. This paper presents an outline of a particular form of image interpretation via mobile devices as a method of skin cancer screening. The use of mobile hardware resources is intrinsically interconnected with the decision making engine built into the processing system. The challenging fundamental problem of computational geometry is in offering a software-hardware solution for image recognition in a complex environment where not all aspects of that environment can fully be captured for use within the algorithm. The unique combination of hardware-software interaction described in this paper brings image processing within such an environment to the point where accurate and stable operation is possible, offering a higher level of flexibility and automation. The Fuzzy logic classification method makes use of a set of features which include fractal parameters derived from generally understood Fractal Theory. The automated learning system is helping to develop the system into one capable of near-autonomous operation. The methods discussed potentially have a wide range of applications in 'machine vision'. However, in this publication, we focus on the development and implementation of a skin cancer screening system that can be used by nonexperts so that in cases where cancer is suspected a patient can immediately be referred to an appropriate specialist.

$Research paper thumbnail of Object recognition using fractal geometry and fuzzy logic$

This thesis describes a novel approach to the object recognition problem for incoherent images us... more This thesis describes a novel approach to the object recognition problem for incoherent images using fractal geometry and fuzzy systems. Although the applications of this approach are general, in this work the method is applied to the evaluation of cytological states associated with cervix uteri diseases, skin cancer and a surface inspection system for quality control in the steel industry. These applications are the basis for industrial work undertaken during the development of this thesis. In each of these applications, the object recognition problem and

GitHub, Jul 14, 2020

This is a basic operating system for a recycled robot based on the Pioneer series of robots e.g. ... more This is a basic operating system for a recycled robot based on the Pioneer series of robots e.g. Pioneer 3 and Peoplebot. The original onboard computer from the Pioneer machines were replaced with Jetson Nano's. These were connected to the Hitachi driver processors using a serial connection via the Jetson's USB. The operating system was wrote in Python as an expandable, easily modified system for basic motion and server reporting

Biological cell analysis has, and is still, an important aspect in medical research and clinical ... more Biological cell analysis has, and is still, an important aspect in medical research and clinical diagnosis. Although cytologists routinely undertake a diagnosis using optical microscopy, human factors make this routine unreliable especially when it involves many consecutive tasks that are monotonous, time consuming and focus on pattern matching tasks where the patterns concerned are not always entirely clear and/or do not necessarily belong to a well defined class. Raman Spectroscopy provides the potential to generate a fundamental representation on the status of cellular conditions through the characteristics of a Raman spectrum generated by the back-scatter of a laser pulse incident on the cell nucleus. However, this approach requires the nucleus of the cell to be accurately targeted from a complex of many hundreds of such cells within a conventional optical field of view as defined by the resolving properties of a microscope. This requires specialist digital image processing methods to be developed and in this paper we discuss a new approach to the processes of object detection, recognition and classification for target detection in cytology using Raman Spectroscopy. In particular, we report on a system designed for the inspection of slides used in a cervical cancer screening system known generally as a 'Pap-smear' test. After providing a short introduction to the pattern recognition in general, we present a unique procedure for automating the targeting process based on an analysis of the principal issues associated with object recognition which include the basic model used and segmentation algorithms derived from the model.

International Joint Conference on Biomedical Engineering Systems and Technologies, 2013

Object recognition in machine vision system and robotic applications has, and is still, an import... more Object recognition in machine vision system and robotic applications has, and is still, an important aspect in automation applications of our everyday life. Although there are a lot of machine vision algorithms there are not always entirely clear and unified solutions for particular applications. This paper is concerned one particular step in image interpretation connected with the convex hull algorithm. This new approach to the process of convex hull step of object recognition offers a wide range of application and improves the accuracy of decision making on later steps. The challenging fundamental problem of computational geometry is offering the solution in this work to solve convex hull procedure for an unknown image polygon. The unique feature of the offered new approach is the flexible intersection of all convex set points of an object on a digital image. The convex combination points remains unknown and allow us to get the real vector space. The image segmentation algorithm and decision making procedure working in conjunction with this new convex hull algorithm will take robotic applications to a higher level of flexibility and automation. We present this unique procedure for automating and a new model of image understanding.

This Conference Paper is brought to you for free and open access by the

We present an approach to object detection and recognition in a digital image using a classificat... more We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the ‘system ’ developed, have a range of applications in ‘machine vision ’ and in this publication, we focus on the development and implementation of a skin cancer screening system that can be used in a general practice by non-experts to ‘filter ’ normal from abnormal cases so that in the latter case, a patient can be referred to a specialist. The paper provides an overview of the system design and includes a link from which interested readers can download and use a demonstration version of the system developed to date.

A novel pattern recognition technique has been deployed in the treatment of cancer tumours to pro... more A novel pattern recognition technique has been deployed in the treatment of cancer tumours to provide improved targeting of ionising radiation and more accurate measurement of the radiation dose. The radiation beams enter the body from different directions to concentrate on the tumour. The centre of the tumour has to be precisely located relatively to patient’s skin surface, so the radiation does not affect healthy tissue and produces successful treatment. Existing methods of 3D dose measurement are highly labor-intensive and generally suffer from low accuracy. In this publication, we propose a new method of 3D measurement of the dose in real-time by using skin pattern recognition technology. The textural pattern of the patient’s skin is analysed from an image sensor in a specially designed camera using Fractal Geometry and Fuzzy logic. A specially designed net sensor is then placed over the area of skin exposed to the treatment in order to measure the radiation dose. The algorithms...

A unique space oriented filer is presented in order to detect and isolate the cell of a nucleus f... more A unique space oriented filer is presented in order to detect and isolate the cell of a nucleus for applications in cytopathology. A classification method for nuclei is then considered based on the application of a set of features which includes certain fractal parameters. Segmentation algorithms are considered in which a self-adjustable sharpening filter is designed to enhance object location. Although the methods discussed and the algorithms developed have a range of applications, in this work we focus the engineering of a system for automating a Papanicolaou screening test using standard optical images

Proceedings of the International Conference on Biomedical Electronics and Devices, 2013

Proceedings of the International Conference on Biomedical Electronics and Devices, 2014

This paper discusses a new approach to the processes of object detection, recognition and classif... more This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image focusing on problem in Cytopathology. A unique self learning procedure is presented in order to incorporate expert knowledge. The classification method is based on the application of a set of features which includes fractal parameters such as the Lacunarity and Fourier dimension. Thus, the approach includes the characterisation of an object in terms of its fractal properties and texture characteristics. The principal issues associated with object recognition are presented which include the basic model and segmentation algorithms. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and a novel technique for the creation and extraction of information from a membership function considered. The methods discussed and the algorithms developed have a range of applications and in this work, we focus the engineering of a system for automating a Papanicolaou screening test.

The detection, recognition and classification of features in a digital image is an important comp... more The detection, recognition and classification of features in a digital image is an important component of quality control systems in production and process engineering and industrial systems monitoring, in general. In this paper, a new pattern recognition system is presented that has been designed for the specific task of monitoring the quality of sheet-steel production in a rolling mill. The system is based on using both the Euclidean and Fractal geometric properties of an imaged object to develop training data that is used in conjunction with a supervised learning procedure based on the application of a fuzzy inference engine. Thus, the classification method includes the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension and thereby incorporates the characterisation of an object in terms of texture that, in this application, has metallurgical significance. The principal issues associated with object recognition are presented including a new segmentation algorithm. The selflearning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and a new technique for the creation and extraction of information from a membership function considered. The methods discussed, and the system developed, have a range of applications in 'machine vision' and automatic inspection. However, in this publication, we focus on the development and implementation of a surface inspection system designed specifically for monitoring surface quality in the manufacture of sheet-steel. For this publication, we include a demonstration version of the system which can be downloaded, installed and utilised by interested readers as discussed in Section VI.

PATTERNS 2011, The Third …, 2011

Object detection, recognition and texture classification is an important aspect of many industria... more Object detection, recognition and texture classification is an important aspect of many industrial quality control systems. In this paper, we report on a system designed for the inspection of surfaces which has a range of applications in the area of metallurgy. The approach considered is based on the application of Fractal Geometry and Fuzzy Logic for texture classification and, in this paper, focuses on the manufacture of rolled steel. The manufacture of high quality metals requires automatic surface inspection for the assessment of quality control. Quality control systems are required for several tasks such as screening defected products, monitoring the manufactures process, sorting information for different applications and product certification and grading for end customers. The system discussed in this paper was developed for the Novolipetck Iron and Still Corporation in Russia and tested with images captured at a rolling mill with metal sheets moving at speed of up to six meters per second and inspected for several defect classes. The classification method used is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension thereby incorporating the characterisation of surface surfaces in terms of their texture. The principal issues associated with texture recognition are presented which includes fast segmentation algorithms. The self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory is also presented and a new technique for the creation and extraction of information from a membership function considered. The methods discussed, and the system developed, have a range of applications in 'machine vision' and automatic inspection. However, in this publication, we focus on the development and implementation of a surface inspection system that can be used in a iron and steel manufacture by non-experts to the automatic recognition system operators.

We present an approach to object detection and recognition in a digital image using a classificat... more We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the 'system' developed, have a range of applications in 'machine vision' and in this publication, we focus on the development and implementation of a skin cancer screening system that can be used in a general practice by non-experts to 'filter' normal from abnormal cases so that in the latter case, a patient can be referred to a specialist. The paper provides an overview of the system design and includes a link from which interested readers can download and use a demonstration version of the system developed to date.

Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies, 2016

Dosimetry in the process of treatment of cancer tumour by ionising radiation. It is important and... more Dosimetry in the process of treatment of cancer tumour by ionising radiation. It is important and sometimes very challenging due to the fact that it is necessary to measure the radiation dose in vivo on small areas on the surface of the composite relief. Recently, in order to reduce the radiation dose to healthy tissues and concentration of the therapeutic effect of radiation directly on the tumour application method of three-dimensional (3D) irradiation started, in which radiation beams enter the body from different directions concentrating on the tumour. New methods of treatment correspondingly require more precise and sophisticated methods of dosimetry. Existing methods of 3D dose measurement are highly labor-intensive and generally suffer from low accuracy. In this paper, we propose the technical method of 3D measurement of the dose in real-time and approaches to build volume model of the dose distribution inside the patient's body using object recognition technique.

This paper discusses a new approach to the processes of object detection, recognition and classif... more This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

We present an approach to object detection and recognition in a digital image using a classificat... more We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the ‘system’ developed, have a range of applications in ‘machine vision’ and in this publication, we focus on the development and implementation of a skin cancer screening system that can be used in a general practice by non-experts to ‘filter’ normal from abnormal cases so that in the latter case, a patient can be referred to a specialist. The paper provides an overview of the system design and includes a link from which interested readers can download and use a demonstration version of the system developed to date.

Proceedings of the International Conference on Biomedical Electronics and Devices

$Research paper thumbnail of Object recognition using fractal geometry and fuzzy logic$

GitHub, Jul 14, 2020

International Joint Conference on Biomedical Engineering Systems and Technologies, 2013

This Conference Paper is brought to you for free and open access by the

Proceedings of the International Conference on Biomedical Electronics and Devices, 2013

Proceedings of the International Conference on Biomedical Electronics and Devices, 2014

PATTERNS 2011, The Third …, 2011

We present an approach to object detection and recognition in a digital image using a classificat... more We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the 'system' developed, have a range of applications in 'machine vision' and in this publication, we focus on the development and implementation of a skin cancer screening system that can be used in a general practice by non-experts to 'filter' normal from abnormal cases so that in the latter case, a patient can be referred to a specialist. The paper provides an overview of the system design and includes a link from which interested readers can download and use a demonstration version of the system developed to date.

Proceedings of the 9th International Joint Conference on Biomedical Engineering Systems and Technologies, 2016

This paper discusses a new approach to the processes of object detection, recognition and classif... more This paper discusses a new approach to the processes of object detection, recognition and classification in a digital image. The classification method is based on the application of a set of features which include fractal parameters such as the Lacunarity and Fractal Dimension. Thus, the approach used, incorporates the characterisation of an object in terms of its texture.

We present an approach to object detection and recognition in a digital image using a classificat... more We present an approach to object detection and recognition in a digital image using a classification method that is based on the application of a set of features that include fractal parameters such as the Lacunarity and Fractal Dimension. The principal issues associated with object recognition are presented and a self-learning procedure for designing a decision making engine using fuzzy logic and membership function theory considered. The methods discussed, and the ‘system’ developed, have a range of applications in ‘machine vision’ and in this publication, we focus on the development and implementation of a skin cancer screening system that can be used in a general practice by non-experts to ‘filter’ normal from abnormal cases so that in the latter case, a patient can be referred to a specialist. The paper provides an overview of the system design and includes a link from which interested readers can download and use a demonstration version of the system developed to date.