: Advancements in image processing and computing has lead to its use in various applications in medical imaging. In the field of ophthalmology, retinal analysis is used for medical diagnosis and detection of the diseases. Various diseases such as diabetic retinopathy, age-related macular degeneration, muscular dystrophy can be easily diagnosed using automated diagnostic systems, thus providing ...

potato image segmentation is an important part of image-based potato defect detection. this paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on genetic algorithm (ga) optimization and morphological operators. the proposed potato color image segmentation is robust against variation of background, distance and ...

Optic disk segmentation plays a key role in the mass screening of individuals with diabetic retinopathy and glaucoma ailments. An efficient hardware-based algorithm for optic disk localization and segmentation would aid for developing an automated retinal image analysis system for real time applications. Herein, TMS320C6416DSK DSP board pixel intensity based fractal analysis algorithm for an au...

Retinal images are analyzed to identify the glaucoma or the diabetic disease. The accuracy of disease detection depends on the extracted features. In this paper, segmentation and mathematical filters based statistical approach is presented to identify the retinal disease. At first stage of this statistical model, the features from retinal image are extracted using segmentation method. This segm...

Image segmentation of retinal blood vessels is a process that can help to predict and diagnose cardiovascular related diseases, such as hypertension and diabetes, which are known to affect the retinal blood vessels' appearance. This work proposes an unsupervised method for the segmentation of retinal vessels images using a combined matched filter, Frangi's filter and Gabor Wavelet filter to enh...

As retinopathies continue to be major causes of visual loss and blindness worldwide, early detection and management of these diseases will help achieve significant reduction of blindness cases. However, an efficient automatic retinal vessel segmentation approach remains a challenge. This paper presents study on the combination of difference image and K-means clustering for the segmentation of r...

Retinal vessel segmentation is critical in detecting retinal blood vessels for a variety of eye disorders, and consistent computerized method required automatic disorder screening. Many methods are implemented, but these only yielded accuracy lack good sensitivity due to the coherence segmentation. Another main factor low proper technique handle low-varying contrast problem. In this study, we p...

Image segmentation is a fundamental approach in the field of image processing and based on user’s application .This paper propose an original and simple segmentation strategy based on the EM approach that resolves many informatics problems about hyperspectral images which are observed by airborne sensors. In a first step, to simplify the input color textured image into a color image without tex...

Computerized segmentation of retinal vessels can help doctors discover diabetic retinopathy, Retinal Tear and Detachment. Because the anatomy is complicated changing, automated vessel still a difficult task. The Expectation-Maximization approach for vascular proposed in this paper, which uses matched filter (MF) that combines Mask based Blood Vessels Extraction with global image threshold to ex...