Image Registration in Hough Space Using Gradient of Images

Shams, Ramtin; Barnes, Nick; Hartley, Richard

doi:10.1109/dicta.2007.4426800

Cited by 8 publications

(4 citation statements)

References 10 publications

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“…Animals were housed overnight at the Animal Resource Center and returned to our laboratory for 24 hours measurements. The field-of-view (FOV) registration was obtained by optical alignment of the SC images at 0 minutes and 24 hours for both experimental and control groups [17][18][19] to prevent erroneous 24 hours measurements. Specific points in the major arteries and veins of the SC images from 24 hours measurement were co-registered with the SC images from 0 minute.…”

Section: Methodsmentioning

confidence: 99%

Perfusion in hamster skin treated with glycerol

et al. 2009

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Section: Methodsmentioning

confidence: 99%

Perfusion in hamster skin treated with glycerol

et al. 2009

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“…al. [5] paper is a good match to our problem definition and we have implemented most of the said registration steps using Hough Transform. But we have used Hough space to obtain the parameters of interest and register in spatial domain, not registered the image in Hough space.…”

Section: Literature Surveymentioning

confidence: 99%

Machine Vision Based Approach for Automated Keypad Inspection

Navghane¹,

Pise²,

Kulkarni³

et al. 2022

IJCDS

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Humans have been traditionally tasked with quality control because it requires judgment. Hence when it comes to manufacturing and quality inspection, Machine Vision plays an important role. However, for the best quality, parameters like lighting, changes in colour, curvature, alignment, required time for flaw detection are various challenging factors. Defects on flat products like keypad labels can be hard for human inspectors to spot easily, reliably due to their random occurrence. It is very hard to scrutinize keypads with a very high degree of detail and different colours within a small area. Hence for the inspection of flaws or even small defects in the keypad, an automated system is required which will select the correct, non-defective samples and reject the defective samples. While working with the images for detection of faulty regions, image subtraction is to be carried out. This is possible if two objects are partially aligned. Hence the need for image registration arises. The main aim of this paper is to register multi-temporal images for minimizing the misalignment of the objects and computation of high correlation factor by Hough Transform based Parameter Extraction (HTPE) and Image Registration using Multilevel Pyramids (IRMP). In the presence of non-uniform lighting conditions the accuracy achieved is 75%.

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“…The mutual information (MI) between both of target and database images is consequently computed to emphasize and finally realize the recognition between target image and its corresponding database image. MI is calculated according to the following equation [30]:…”

Section: A Implementation Of Proposed Automatic Target Recognition Amentioning

confidence: 99%

New Automatic Target Recognition Approach based on Hough Transform and Mutual Information

Bahy¹

2018

IJIGSP

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This paper presents a new automatic target recognition approach based on Hough transform and mutual information. The Hough transform groups the extracted edge points in edged images to an appropriate set of lines which helps in features extraction and matching processes in both of target and stored database images. This gives an initial indication about realization and recognition between target image and its corresponding database image. Mutual information is used to emphasize the recognition of the target image and its verification with its corresponding database image. The proposed recognition approach passed through five stages which are: edge detection by Sobel edge detector, thinning as a morphological operation, Hough transformation, matching process and finally measuring the mutual information between target and the available database images. The experimental results proved that, the target recognition is realized and gives more accurate and successful recognition rate than other recent recognition techniques which are based on stable edge weighted HOG.

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Image Registration in Hough Space Using Gradient of Images

Cited by 8 publications

References 10 publications

Perfusion in hamster skin treated with glycerol

Perfusion in hamster skin treated with glycerol

Machine Vision Based Approach for Automated Keypad Inspection

New Automatic Target Recognition Approach based on Hough Transform and Mutual Information

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