Glaucoma is one of the most dangerous eye diseases. It occurs as a result of an imbalance in the drainage and flow of the retinal fluid. Consequently, intraocular pressure is generated, which is a significant risk factor for glaucoma. Intraocular pressure causes progressive damage to the optic nerve head, thus leading to vision loss in the advanced stages. Glaucoma does not give any signs of disease in the early stages, so it is called "the Silent Thief of Sight". Therefore, early diagnosis and treatment of retinal eye disease is extremely important to prevent vision loss. Many articles aim to analyze fundus retinal images and diagnose glaucoma. This review can be used as a guideline to help diagnose glaucoma. It presents 63 artic

Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

A super pixel can be defined as a group of pixels, which have similar characteristics, which can be very helpful for image segmentation. It is generally color based segmentation as well as other features like texture, statistics…etc .There are many algorithms available to segment super pixels like Simple Linear Iterative Clustering (SLIC) super pixels and Density-Based Spatial Clustering of Application with Noise (DBSCAN). SLIC algorithm essentially relay on choosing N random or regular seeds points covering the used image for segmentation. In this paper Split and Merge algorithm was used instead to overcome determination the seed point's location and numbers as well as other used parameters. The overall results were better from the SL

     Steganography is a technique to hide a secret message within a different multimedia carrier so that the secret message cannot be identified. The goals of steganography techniques include improvements in imperceptibility, information hiding, capacity, security, and robustness. In spite of numerous secure methodologies that have been introduced, there are ongoing attempts to develop these techniques to make them more secure and robust. This paper introduces a color image steganographic method based on a secret map, namely 3-D cat. The proposed method aims to embed data using a secure structure of chaotic steganography, ensuring better security. Rather than using the complete image for data hiding, the selection of

The steganography (text in image hiding) methods still considered important issues to the researchers at the present time. The steganography methods were varied in its hiding styles from a simple to complex techniques that are resistant to potential attacks. In current research the attack on the host's secret text problem didn’t considered, but an improved text hiding within the image have highly confidential was proposed and implemented companied with a strong password method, so as to ensure no change will be made in the pixel values of the host image after text hiding. The phrase “highly confidential” denoted to the low suspicious it has been performed may be found in the covered image. The Experimental results show that the covere

The field of autonomous robotic systems has advanced tremendously in the last few years, allowing them to perform complicated tasks in various contexts. One of the most important and useful applications of guide robots is the support of the blind. The successful implementation of this study requires a more accurate and powerful self-localization system for guide robots in indoor environments. This paper proposes a self-localization system for guide robots.  To successfully implement this study, images were collected from the perspective of a robot inside a room, and a deep learning system such as a convolutional neural network (CNN) was used. An image-based self-localization guide robot image-classification system delivers a more accura

Iris detection is considered as challenging image processing task. In this study efficient method was suggested to detect iris and recognition it. This method depending on seed filling algorithm and circular area detection, where the color image converted to gray image, and then the gray image is converted to binary image. The seed filling is applied of the binary image and the position of detected object binary region (ROI) is localized in term of it is center coordinates are radii (i.e., the inner and out radius). To find the localization efficiency of suggested method has been used the coefficient of variation (CV) for radius iris for evaluation. The test results indicated that is suggested method is good for the iris detection.

The basic solution to overcome difficult issues related to huge size of digital images is to recruited image compression techniques to reduce images size for efficient storage and fast transmission. In this paper, a new scheme of pixel base technique is proposed for grayscale image compression that implicitly utilize hybrid techniques of spatial modelling base technique of minimum residual along with transformed technique of Discrete Wavelet Transform (DWT) that also impels mixed between lossless and lossy techniques to ensure highly performance in terms of compression ratio and quality. The proposed technique has been applied on a set of standard test images and the results obtained are significantly encourage compared with Joint P

Most includeding techniques of digital watermark even now working through the direct inclusion in the pixel without taking into account the level of compression (attack) that can go wrong, which makes digital watermark can be discarded easily. In this research, a method was proposed to overcome this problem, which is based on DCT (after image partitioned into non overlapped blocks with size 8×8 pixel), accompanied by a quantization method. The watermark (digital image) is embedded in DCT frequency domain seeking the blocks have highest standard deviation (the checking is only on the AC coefficients) within a predetermined threshold value, then the covered image will compressed (attacked) varying degrees of compression. The suggested met

Localization is an essential issue in pervasive computing application. FM performs worse in some indoor environment when its structure is same to some extent the outdoor environment like shopping mall. Furthermore, FM signal are less varied over time, low power consumption and less effected by human and small object presence when it compared to Wi-Fi. Consequently, this paper focuses on FM radio signal technique and its characteristics that make it suitable to be used for indoor localization, its benefits, areas of applications and limitations.