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Object Motion estimation using edge detection and background subtraction with block matching algorithm

100%

Thapliyal S. , Pundir Y. P. , Bahuguna A. S. , Semwal S.

tom Vol. 10

345--348

Detection of an object motion is the growing research field of image processing which revealed the several applications. Several techniques (including the proposed one) are discussed so far in literatures. In this paper the edge detection and frame differencing also known as background subtraction technique with block matching algorithm has been implemented to detect the object motion. The object taken for experimentation is arbitrary having no fixed shape and size. The MATLAB output result showing the practicability of the both algorithms.

EBMBDT : Effective Block Matching Based Denoising Technique using Dual Tree Complex Wavelet Transform

75%

Selvi M.

tom Vol. 23, No. 3/4

23--41

In processing and investigation of digital image denoising of images is hence very important. In this paper, we propose a Hybrid denoising technique by using Dual Tree Complex Wavelet Transform (DTCWT) and Block Matching Algorithm (BMA). DTCWT and BMA is a method to identify the noisy pixel information and remove the noise in the image. The noisy image is given as input at first. Then, bring together the comparable image blocks into the load. Afterwards Complex Wavelet Transform (CWT) is applied to each block in the group. The analytic filters are made use of by CWT, i.e. their real and imaginary parts from the Hilbert Transform (HT) pair, defending magnitude-phase representation, shift invariance, and no aliasing. After that, adaptive thresholding is applied to enhance the image in which the denoising result is visually far superior. The proposed method has been compared with our previous denoising technique with Gaussian and salt-pepper noise. From the results, we can conclude that the proposed de-noising technique have shown better values in the performance analysis.

Pomiary przestrzenne w polu obserwacyjnym stereoendoskopu

63%

Goral A.

tom R. 91, nr 5

13-16

W pracy przedstawiono procedurę trójwymiarowej metrycznej rekonstrukcji powierzchni na podstawie zapisu wideo ze stereoendoskopu stosowanego w chirurgii minimalnie inwazyjnej. Metoda bazuje na dopasowaniu obszarami fragmentów obrazów. Wyniki rekonstrukcji porównano z danymi uzyskanymi dla tego samego obiektu metodą referencyjną. Średni błąd rekonstrukcji uzyskany dla poszczególnych klatek sekwencji wynosi od 2,1 do 4,2 mm.

In this work, we present a procedure for 3-dimensional metric surface reconstruction based on video data from a stereoendoscope used in minimally invasive surgery. The reconstruction is based on stereo block matching algorithm. The results of the reconstruction were compared to a reference data set obtained simultaneously for the same object. The mean reconstruction error obtained for individual frames falls within the range of 2.1 to 4.2 mm.