- Wear Mechanism Identification Using Advanced Image Segmentation Techniques – An Innovative Approach
1P. Amuthakkannan, 2M.Pallikonda Rajasekaran, 3T.Arun Prasath, 4B.Perumal, 5G.Vishnuvarthanan, 6V.Muneeswaran,7P.Rajeshkumar, 8V.Arumuga Prabhu and 9Selvakumar, 1,8Centre for Composite materials and 2,3,4,5,6,7,9Centre for image Processing and VLSI design, Kalasalingam University, Virudhunagar,India.
This work made an attempt to identify the wear mechanism of the Aluminium metal matrix composites using advanced image processing techniques. Basalt fiber reinforced Aluminium metal matrix composites was fabricated through stirrer casting techniques with varying weight percentages. Sliding Wear characterization analysis was tested in Pin on Disc wear test apparatus. The image segmentation technique namely K-mean clustering which has implemented for grouping the similar property of pixels together. Particle Swarm Optimization(PSO) is the process to improve the segmentation results by executing the computation iteratively until the best fitness achieved, according to these analysis the wear mechanism of the composites were observed the wear pattern; types of the wear clearly can identify with the used imaging techniques. It can concluded that the based on the wear pattern different imagining techniques need to be adopted.
- Tone Mapping Comparison By Contrast Assessment Method Adapted To Low Visual Acuity
Imad Benkhaled1, Isabelle Marc1 and Dominique Lafon2 ,1LGI2P ECOLE DES MINES D’ALES –FRANCE ,2C2MA ECOLE DES MINES D’ALES –FRANCE
Some visual pathologies such as glaucoma or Retinitis Pigmentosa induce high level of sensibility to light variations. Imaging technologies and methods may be used to alleviate discomfort problems faced by visually impaired people due to glare or low acuity in dark areas, if the high dynamic range of real world luminance can be mapped into a more limited range. This paper aims first to find a method for objective contrast assessment that accounts for low visual acuity. In a second part, the effects of different tone mapping on contrast are compared.
- An Investigation of Watermarking Medical Images
Majdi Al-qdah, Department of Computer Engineering, University of Tabuk, Tabuk City, KSA
This paper presents the results of watermarking selected various medical cover images with simple string of letters image (patients' medical data) using a combination of the Discrete Wavelet Transform (DWT) Discrete Cosine Transform (DCT) and singular value decomposition (SVD). The visual quality of the watermarked images (before and after attacks) was analyzed using PSNR and four visual quality metrics (WSNR, MSSIM, PSNR-HVS-M, and PSNR-HVS). The PSNR, PSNR-HVS-M, PSNR-HVS, and WSNR average values of the watermarked medical images before attacks were about the 32 db, 35 db, and 42 db, 40 db respectively; while the MSSM index indicated a similarity of more than 97% between the original and watermarked images. The metric values decreased significantly after attacking the images with various operations but the watermark image could be retrieved after almost all attacks. Thus, the initial results indicate that watermarking medical images with the patients' data does not significantly affect their visual quality and they still can be utilized for their medical purpose.
- An Adaptive Method For Under-Sampling Of Mri Images Based On Compressive Sensing
Mohammad Reza Ghavidel Aghdam, Tohid Yousefi Rezaii,Faculty of Electrical and Computer Engineering University of Tabriz, Tabriz, Iran
Compressive sensing (CS) utilizes sparsity of MRI images for accurate reconstruction of under-sampled k-space data. In order to use MRI in CS, k-space image should be sampled and then CS techniques should be applied. Although most common sampling methods in CS framework may have good properties, they are not optimal in image reconstruction due to their finite data. In this paper, a new method will be presented for adaptive sampling consisting of two updating steps: namely as sampling method and image update steps. Given reconstructions are used in sampling update step and fixed sampling method are used in image update step besides convergence in PSNR. Wavelet transform and image blocking are also applied. The blocks used in the adaptive stage are chosen spirally leading to less calculations and maintaining low-frequency image information in the centre of k-space. Simulation results indicated 7.5dB improvement in PSNR reconstruction using adaptive sampling.
- An Image Processing Scheme For Skin Fungal Disease Identification
A.A.M.A.S.S.Perera, L.A.Ranasinghe,T.K.H.Nimeshika, D.M.Dhanushka Dissanayake, Namalie Walgampaya, Department of Software Engineering, Sri Lanka Institute of Information Technology (SLIIT), Malabe, Sri Lanka.
Nowadays, skin fungal diseases are mostly found in people of tropical countries like Sri Lanka. A skin fungal disease is a particular kind of illness caused by fungus. These diseases have various dangerous effects on the skin and keep on spreading over time. It becomes important to identify these diseases at their initial stage to control it from spreading. This paper presents an automated skin fungal disease identification system implemented to speedup the diagnosis process by identifying skin fungal infections in digital images. An image of the diseased skin lesion is acquired and a comprehensivecomputer vision and image processing scheme is used to process the image for the disease identification.This includes colour analysis using RGB and HSV colour models, texture classification using Grey Level Run Length Matrix, Grey Level Co-Occurrence Matrix and Local Binary Pattern, Object detection, Shape Identification and many more.This paper presents the approach and its outcome for identification of four most common skin fungal infections, namely, Tinea Corporis, Sporotrichosis, Malassezia and Onychomycosis. The main intention of this research is to provide an automated skin fungal disease identification system that increase the diagnostic quality, shorten the time-to-diagnosis and improve the efficiency of detection and successful treatment for skin fungal diseases.