A Simple Image Encryption Based on Binary Image Affine Transformation and Zigzag Process

In this paper, we propose a new and simple method for image encryption. It uses an external secret key of 128 bits long and an internal secret key. The novelties of the proposed encryption process are the methods used to extract an internal key to apply the zigzag process, affine transformation, and substitution-diffusion process. Initially, an original gray-scale image is converted into binary images. An internal secret key is extracted from binary images. The two keys are combined to compute the substitution-diffusion keys. The zigzag process is firstly applied on each binary image. Using an external key, every zigzag binary image is reflected or rotated and a new gray-scale image is reconstructed. The new image is divided into many nonoverlapping subblocks, and each subblock uses its own key to take out a substitution-diffusion process. We tested our algorithms on many biomedical and nonmedical images. It is seen from evaluation metrics that the proposed image encryption scheme provides good statistical and diffusion properties and can resist many kinds of attacks. It is an efficient and secure scheme for real-time encryption and transmission of biomedical images in telemedicine.

Script Identification of Camera Based Bilingual Document Images Using SFTA Features

In this article, the exhaustive experiment is carried out to test the performance of the Segmentation based Fractal Texture Analysis (SFTA) features with nt = 4 pairs, and nt = 8 pairs, geometric features and their combinations. A unified algorithm is designed to identify the scripts of the camera captured bi-lingual document image containing International language English with each one of Hindi, Kannada, Telugu, Malayalam, Bengali, Oriya, Punjabi, and Urdu scripts. The SFTA algorithm decomposes the input image into a set of binary images from which the fractal dimension of the resulting regions are computed in order to describe the segmented texture patterns. This motivates use of the SFTA features as the texture features to identify the scripts of the camera-based document image, which has an effect of non-homogeneous illumination (Resolution). An experiment is carried on eleven scripts each with 1000 sample images of block sizes 128 × 128, 256 × 256, 512 × 512 and 1024 × 1024. It is observed that the block size 512 × 512 gives the maximum accuracy of 86.45% for Gujarathi and English script combination and is the optimal size. The novelty of this article is that unified algorithm is developed for the script identification of bilingual document images.

Porosity of the porous carbonate rocks in the Jingfengqiao–Baidiao area based on finite automata

This study is based on the processing of computed microtomography images of rock samples. In this study, a finite automation is constructed using the grey value, red-green-blue (RGB) value and Euler number of polarized images of carbonate rocks from the Jingfengqiao–Baidiao area. The finite automaton is used to perform black and white binary processing of the polarized images of the carbonate rocks. The porosity of the carbonate rock is calculated based on the black and white binarization processing results of the polarized images of the carbonate rocks. The obtained porosity is compared with the carbonate porosity obtained by use of the traditional carbonate research method. When the two porosities are close, the image processing threshold of the finite automata is considered to be credible. Based on the finite automata established using the image processing threshold, the black and white binary images of the polarized images of the carbonate rocks are used to establish a rock pore image using I mage J2X. The polarized images of the carbonate rocks are classified according to their RGB values using the finite automata for the porosity classification, and the obtained images are used as textures to paste onto a cube to construct a three-dimensional data model of the carbonate rocks. This study also uses 16S rDNA analysis to verify the formation mechanism of the carbonate pores in the Jingfengqiao–Baidiao area. The results of the 16S rDNA analysis show that the pores in the carbonate rocks in the Jingfengqiao–Baidiao area are closely related to microorganisms, represented by denitrifying bacteria.

Improved playback uniformity of random-phase free holograms by pixel separation method

Random-phase free computer-generated holograms offer excellent quality of virtually noise-free playback of low-frequency images, but have limited efficiency in the case of highly contrast binary images with dominant high spatial frequencies. Introduction of weak random phase allows the partial suppression of this problem, but causes strong noise in the outcome. Here we present the influence of pixel separation technique on the uniformity of far field reconstructions from such random-phase free holograms. We show the improved image quality with no additional speckle noise. Full Text: PDF ReferencesJ.W. Goodman, Roberts and Company (2005). DirectLink R.W. Gerchberg, W.O. Saxton, "A practical algorithm for the determination of phase from image and diffraction plane pictures", Optik 35, 237 (1972). DirectLink M. Makowski, "Minimized speckle noise in lens-less holographic projection by pixel separation", Opt. Express 21, 29205 (2013). CrossRef I. Ducin, T. Shimobaba, M. Makowski, K. Kakarenko, A. Kowalczyk, Jaroslaw Suszek, M. Bieda, A. Kolodziejczyk, M. Sypek, "Holographic projection of images with step-less zoom and noise suppression by pixel separation", Opt. Comm. 340, 131 (2015). CrossRef T. Shimobaba, T. Ito, "Random phase-free computer-generated hologram", Opt. Express 23, 9549 (2015). CrossRef T. Shimobaba, T. Kakue, Y. Endo, R. Hirayama, D. Hiyama, S. Hasegawa, Y. Nagahama, M. Sano, M. Oikawa, T. Sugie, T. Ito, "Random phase-free kinoform for large objects", Opt. Express 23, 17269 (2015). CrossRef M. Sypek, "Light propagation in the Fresnel region. New numerical approach", Opt. Comm. 116, 43 (1995). CrossRef K. Matsushima, T. Shimobaba, "Band-Limited Angular Spectrum Method for Numerical Simulation of Free-Space Propagation in Far and Near Fields", Opt. Express 17, 19662 (2009). CrossRef

Classification of Dermoscopic Image of Skin Cancer Using the GLCM Method and Multi-SVM Algorithm

The development of abnormal skin pigment cells can cause a skin cancer called melanoma. Melanoma can be cured if diagnosed and treated in its early stages. Various studies using various technologies have been developed to conduct early detection of melanoma. This research was conducted to diagnose melanoma skin cancer with digital image processing techniques on the dermoscopic image of skin cancer. The diagnosis is made by classifying dermoscopic images based on the types of Common Nevus, Atypical Nevus or Melanoma. Pre-processing is done by changing the RGB image to grayscale (grayscaling), smoothing image using median filtering, and image segmentation based on binary images of skin lesions. The value of Contrast, Correlation, Energy and Homogeneity obtained from the texture feature extraction of the GLCM method is used in the next step, which is the classification process with the Multi-SVM algorithm. The proposed research method shows high accuracy results in diagnosing skin cancer

Melt Pool Features Analysis Using a High Speed Coaxial Monitoring System for Laser Powder Bed Fusion of Ti-6Al-4V Grade 23

In laser powder bed fusion (LPBF), defects such as pores or cracks can seriously affect the final part quality and lifetime. Keyhole porosity, being one type of porosity defects in LPBF, results from excessive energy density which may be due to changes in process parameters (laser power and scan speed) and/or result from the part’s geometry and/or hatching strategies. To study the possible occurrence of keyhole pores, experimental work as well as simulations were carried out for optimum and high volumetric energy density conditions in Ti-6Al-4V grade 23. By decreasing the scanning speed from 1000 mm/s to 500 mm/s for a fixed laser power of 170 W, keyhole porosities are formed and later observed by X-ray computed tomography. Melt pool images are recorded in real-time during the LPBF process by using a high speed coaxial Near-Infrared (NIR) camera monitoring system. The recorded images are then pre-processed using a set of image processing steps to generate binary images. From the binary images, geometrical features of the melt pool and features that characterize the spatter particles formation and ejection from the melt pool are calculated. The experimental data clearly show spatter patterns in case of keyhole porosity formation at low scan speed. A correlation between the number of pores and the amount of spatter is observed. Besides the experimental work, a previously developed, high fidelity finite volume numerical model was used to simulate the melt pool dynamics with similar process parameters as in the experiment. Simulation results illustrate and confirm the keyhole porosity formation by decreasing laser scan speed.

Pemanfaatan citra kamera inframerah thermal (kit) untuk mendeteksi area inflamasi pada tubuh manusia

Inflammation is an indication of an abnormality in the human body. Cases of inflammation occur accompanied by changes in temperature on the surface of the body. The location and location of the spread of inflammation cannot be seen solely by the human eye in detail. An imaging modality tool that is suitable for use in observing this problem is needed. In this study, the Thermal Infrared Camera (TIC) is used as an imaging modality. Samples in the form of a pair of legs in which one part of inflammation occurs are used as research objects. TIC is an imaging modality tool that can detect temperatures on the surface of an object quickly and is nondestructive. The results of the TIC image are processed using the global thresholding image processing method to distinguish between the inflammatory areas and normal areas more specifically. The results displayed indicate that there are differences in the image between the area of inflammation with the normal area of the patient's feet. The results of image processing data in the form of binary images show between the inflammatory area represented by white and vice versa the normal area represented by black. A comparison between the two conditions of the patient's feet before and after recovery shows the shrinkage of the area. There are two main results obtained in the exploration of this research, which is successful in distinguishing the inflammatory area from the normal area and the progress of recovery from the legs of the affected patient.

Multiscale Research on Pore Structure Characteristics and Permeability Prediction of Sandstone

The random existence of many irregular pore structures in geotechnical materials has a decisive influence on its permeability and other macroscopic properties. The analysis and characterization of the micropore structure of the material and its permeability are of great significance for geotechnical engineering. In this study, digital images with different magnifications were used to examine the pore structure and permeability of sandstone samples. The image processing method is used to obtain binary images, and then, the pore size distribution method is used to calculate the pore size distribution. Therefore, based on the Hagen-Poiseuille formula, we get the prediction value of material’s permeability and compare it with the value obtained from mercury intrusion porosimetry (MIP). It is found that different microscopic images with different magnification and various statistical methods of pore size have a specific influence on the characterization of pore structure and permeability prediction. The porosity of different magnifications is not the same, and the results obtained at higher magnifications are more consistent with the results obtained with MIP. With the increase of magnification, we can observe more pores in large sizes. The effect of CPSD (continuous pore size distribution) in pore size statistics is better than that of DPSD (discrete pore size distribution). In permeability prediction, the prediction result of higher magnification images are closer to the instrument test value, and the value of DPSD is more significant than that of CPSD. In future research, an appropriate method should be selected to obtain a reasonable prediction of the permeability of the target material.

Multifeature Detection of Microaneurysms Based on Improved SSA

The early diagnosis of retinopathy is crucial to the prevention and treatment of diabetic retinopathy. The low proportion of positive cases in the asymmetric microaneurysm detection problem causes preprocessing to treat microaneurysms as noise to be eliminated. To obtain a binary image containing microaneurysms, the object was segmented by a symmetry algorithm, which is a combination of the connected components and SSA methods. Next, a candidate microaneurysm set was extracted by multifeature clustering of binary images. Finally, the candidate microaneurysms were mapped to the Radon frequency domain to achieve microaneurysm detection. In order to verify the feasibility of the algorithm, a comparative experiment was conducted on the combination of the connected components and SSA methods. In addition, PSNR, FSIM, SSIM, fitness value, average CPU time and other indicators were used as evaluation standards. The results showed that the overall performance of the binary image obtained by the algorithm was the best. Last but not least, the accuracy of the detection method for microaneurysms in this paper reached up to 93.24%, which was better than that of several classic microaneurysm detection methods in the same period.