Query: eye image processing

title: Spatio Temporal Fish Eye Image Processing Based on Neural Network
abstract: In this paper, we describe an approach to correct the distortion in fish eye image. Due to pros of large FOV (field of view) fish eye camera is widely used in computer vision discipline. However, the serious distortion in fish eye image set up barriers to image processing. This paper focus on adapting neural network for correcting distortions in fish eye image. Up to now, traditional correction models such as latitude longitude, sphere and grid template establish a certain model that is ideal and may not fit the reality situation. The method used in our study is known as neural network. Instead of approximately regarding the fish eye distortion model as high order polynomial function, we use neural network to learn the relationship between the distorted and corrected image. The mean square error for the difference between the corrected and ideal points is 4.1345 pixel per point, which is much smaller than the result of polynomial model (32.0809 pixel per point) and the run time for this algorithm is moderate. The results of the experiment indicate that correction model based on neural network can solve the fish eye distortion in an acceptable error and high efficiency.

title: Reproducible pipelines for compound eye image processing

title: Fish freshness estimation using eye image processing under white and UV lightings
abstract: A non destructive method of estimating the freshness of fish is required for appropriate price setting and food safety. In particular, for determining the possibility of eating raw fish (sashimi) freshness estimation is critical. We studied such an estimation method by capturing images of fish eyes and performing image processing using the temporal changes of the luminance of pupil and iris. To detect subtle non visible changes of these features, we used UV (375 nm) light illumination in addition to visible white light illumination. Polarization and two channel LED techniques were used to remove strong specular reflection from the cornea of the eye and from clear plastic wrap used to cover the fish to maintain humidity. Pupil and iris regions were automatically detected separately by image processing after the specular reflection removal process, and two types of eye contrast were defined as the ratio of mean and median pixel values of each region. Experiments using 16 Japanese dace (Tribolodon hakonensis) at 23 and 85% humidity for 24 hours were performed. The eye contrast of raw fish increase non linearly in the initial period and then decreased; however, that of frozen thawed fish decreased linearly throughout 24 hours, regardless of the lighting. Interestingly, the eye contrast using UV light showed a higher correlation with time than that using white light only in the case of raw fish within the early 6 hour period postmortem. These results show the possibility of estimating fish freshness in the initial stage when fish are eaten raw using white and UV lightings.

title: The eye image processing method and apparatus
abstract: Example embodiments provide an image processing method and apparatus of the eye according to the present invention, the method comprising: determining orbital region of an image; acquiring a first image of the orbital region mask; at least the first mask image is determined according to the orbital region a first abnormality region; mask image corresponding to the first abnormality determination conditions to a first region of the eye abnormality candidate area of the eye at least a first abnormal region, wherein the first abnormality candidate region satisfies the eye All abnormality determination condition determination condition eye region image corresponding to the first mask; determining the first candidate for the anomaly of orbital eye region when the confidence region abnormal eye candidate region is greater than the first predetermined value VII abnormal eye area. Method and apparatus embodiments of the present invention is able to locate the eye region abnormal eye image more accurately, to provide accurate position information to process the abnormal eye.

title: Image Processing on Eye Image Using SURFFeature Extraction
abstract: Mobile cloud computing (MCC) is an integration of the concept of cloud computing and mobile computing. When user is able to access cloud services through mobile phone on the basis of pay as per the use then we can see there the use of MCC. As users store their data in the cloud security is an important issue. To overcome this issue the biometric identification method is proposed where eye image is used as biometric input. The image goes through some image processing steps required to extract its features. This paper proposed an algorithm required for image processing.

title: The naked eye image processing method and apparatus of 3d
abstract: Ben Shen Qing Gong Kai Liao Yi Chong Luo Yan 3DTu Xiang De Chu Li Fang Fa Ji Zhuang Zhi ,Qi Zhong ,Gai Suo Shu Fang Fa Ying Yong Yu Dian Zi Xian Shi She Bei ,Suo Shu Fang Fa Bao Gua :Huo Qu NGe Yong Hu De Ren Yan Wei Zhi Xin Xi ,NWei Da Yu Deng Yu 1De Zheng Shu ;Gen Ju Suo Shu NGe Yong Hu De Ren Yan Wei Zhi Xin Xi ,Pan Duan Suo Shu NGe Yong Hu Dui Ying De NGe Shi Qu Dui Shi Fou Wei Zheng Shi Qu ;Ruo Suo Shu NGe Shi Qu Dui Zhong You MGe Shi Qu Dui Chu Yu Suo Shu Zheng Shi Qu ,Diao Zheng You Suo Shu Di iGe Shi Qu Dui Liang Ce De Xiang Lin Shi Qu He Di iGe Shi Qu Dui Gou Cheng De Shi Qu Zhong De Zhi Shao Yi Ge Shi Qu Tu Xiang ,Qi Zhong ,1<=M<=N,1<=i<=M,Bing Qie i,MDu Wei Zheng Shu ;Ruo Suo Shu NGe Shi Qu Dui Zhong You PGe Shi Qu Dui Chu Yu Suo Shu Ni Bian Qu ,Diao Zheng You Suo Shu Di kGe Shi Qu Dui Liang Ce De Xiang Lin Shi Qu He Di kGe Shi Qu Dui Gou Cheng De Shi Qu Zhong De Zhi Shao Yi Ge Shi Qu Tu Xiang ,Qi Zhong ,1<=P<=N,1<=k<=M,Bing Qie k,PDu Wei Zheng Shu

title: Detection of Diabetic Retinopathy and Maculopathy in Eye Fundus Images Using Fuzzy Image Processing
abstract: Diabetic retinopathy is a damage of the retina and it is one of the serious consequences of the diabetes. Early detection of diabetic retinopathy is extremely important in order to prevent premature visual loss and blindness. This paper presents a novel automatic detection of diabetic retinopathy and maculopathy in eye fundus images using fuzzy image processing. The detection of maculopathy is essential as it will eventually cause loss of vision if the affected macula is not timely treated. The developed system consists of image acquisition, image preprocessing with a combination of fuzzy techniques, feature extraction, and image classification by using several machine learning techniques. The fuzzy based image processing decision support system will assist in the diabetic retinopathy screening and reduce the burden borne by the screening team.

title: Structural design and image processing of a spherical artificial compound eye
abstract: This manuscript presents a design method and corresponding image processing algorithms of a spherical artificial compound eye. The artificial compound eye is composed of multi dimensional sub eye imaging channels pointing to different directions. By using the principle of geometrical optics and imaging optics, the design method of the multi dimensional imaging structure was analyzed. To satisfy the practical requirement of the structure, the image processing algorithm based on the segmentation rotation projection technology was studied. In order to validate the above design method and image processing algorithm, a spherical compound eye consisting of 37 imaging channels was fabricated and the corresponding imaging experiments were carried out. The results show that the field of view (FOV) of the imaging structure is up to 118 degrees and the structure meets the practical requirements.

title: Sky Eye: image processing software for amateur astronomers
abstract: The SkyEye project is an attempt to create software for educational and amateur variable stars research. Easy graphical interface, automation of many actions and possibility of using low cost internet cameras makes this software suitable for students and amateur astronomers for observations, measurements and data analysis. The goal is achieved by extending AudeLa project with additional shared libraries written in C/C+ and TCL scripts, much effort was made in order to ensure compatibility with different operating systems, Linux and Windows. The project was developed in the framework of the "Pi of the Sky" collaboration.

title: Review of image processing techniques for automatic detection of eye diseases
abstract: The review paper describes the application of image processing techniques for automatic detection of eye diseases. Large percentages of people suffer from eye diseases in rural and semi urban areas in India as well as world over. Image processing techniques greatly help diagnosing various eye diseases. Current diagnosis of retinal disease relies strongly upon optical imaging methods due to the photon sensing nature of the eye over a wide band of wavelengths. The key image processing elements to detect eye diseases include image registration, fusion, segmentation, feature extraction, enhancement, pattern matching, image classification, analysis and statistical measurements. In developing and under developing countries large number of people are suffering from ophthalmic diseases like Glaucoma, Age related Macular Degeneration (AMD) Diabetic Retinopathy, Diabetic hypertension. A large deficit of ophthalmologists exists in these regions. Year after year the number of medical assistants is decreasing, while demand for healthcare is increasing and expected to touch 40% by 2020. Low cost instrumentation with internet and mobile enabled network connectivity with above techniques can help patients in rural and semi urban areas to access well equipped and sophisticated hospitals in cities