Irregular patterns learning and matching in an example vision system

Zorski, Witold; Murawski, K.

doi:10.1109/mmar.2013.6669986

Cited by 5 publications

(2 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In order to enrich the method an extension about identification of the detected object may be added using a method similar to one described in [23]. Another challenge is the problem of tracking multiple independent objects [20], [21].…”

Section: B Cuda Implementation Supported By the Npp Librarymentioning

confidence: 99%

Movement Tracking in Terrain Conditions Accelerated with CUDA

Sklodowski

Zorski

2014

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

The paper presents a solution to the problem of movement tracking in images acquired from video cameras monitoring outside terrain. The solution is resistant to such adverse factors as: leaves fluttering, grass waving, smoke or fog, movement of clouds etc. The presented solution is based on well known image processing methods, nevertheless the key was the use of an appropriate conduct procedure. In order to obtain a real-time system the CUDA technology was involved.

show abstract

Section: B Cuda Implementation Supported By the Npp Librarymentioning

confidence: 99%

Movement Tracking in Terrain Conditions Accelerated with CUDA

Sklodowski

Zorski

2014

Annals of Computer Science and Information Systems

View full text Add to dashboard Cite

show abstract

“…The parameter space is defined for translation, rotation, and (alternatively) scale of the pattern in the image. Accumulator values for above coordinates are calculated using pixels matching method [17]. The problem is the time complexity of an algorithm and the possible solution is use of CUDA technology.…”

Section: Introductionmentioning

confidence: 99%

Unknown scale objects recognition using massively parallel processing with CUDA

Zorski¹,

Sklodowski

2014

2014 19th International Conference on Methods and Models in Automation and Robotics (MMAR)

Self Cite

View full text Add to dashboard Cite

The paper presents a method of irregular patterns creation and matching in an example computer vision system designed for unknown scale objects recognition. The matching process is based on the Hough transform for irregular objects with a parameter space defined by translation, rotation and scaling operations. The high efficiency of the technique allows for poor quality or highly complex images to be analysed. The technique may be used in robot vision systems with unknown scale of the scene, identification systems or for image analysis, directly on grey-level images. In order to guarantee the performance the process of patterns matching is supported by massively parallel processing with the CUDA technology.

show abstract