Hard Exudate Extraction from Fundus Images using Watershed Transform

Diabetic Retinopathy is a medical condition which affects the eyes due to increased blood sugar levels. This is characterized by presence of exudates - deposits of lipids in the posterior pole of the retina. If this ailment is not treated in earlier stages these deposits can cause blurred vision or even permanent blindness. This paper concentrates on extraction of hard exudates and optic disc from the retinal images of eyes using Marker based Watershed approach, which uses the minima imposition method to create mask and marker. The varying contrast across all the images has been taken care by a non-linear equation. Once these bright objects have been extracted from fundus images, area estimation is performed to eliminate the optic disk, thus retaining only exudates. These images have been procured from publicly available databases. Though software systems are easy to install, they prove to be expensive in terms of time and cost; thus this method has also been implemented on FPGA for an on-chip solution. The precision and sensitivity for exudate extraction sans optic disk are found to be 92.4% and 83.78% respectively.  Though other techniques exist which provide better accuracy, the method described in this paper is found to be hardware friendly in comparison with other proven methods. Few steps of the algorithm developed are implemented on FPGA to provide an embedded system approach to this work, considering the advantages of a hardware-software combination

Detection of brain stroke in the MRI image using FPGA

One of the most important difficulties which doctors face in diagnosing is the analysis and diagnosis of brain stroke in magnetic resonance imaging (MRI) images. Brain stroke is the interruption of blood flow to parts of the brain that causes cell death. To make the diagnosis easier for doctors, many researchers have treated MRI images with some filters by using Matlab program to improve the images and make them more obvious to facilitate diagnosis by doctors. This paper introduces a digital system using hardware concepts to clarify the brain stroke in MRI image. Field programmable gate arrays (FPGA) is used to implement the system which is divided into four phases: preprocessing, adjust image, median filter, and morphological filters alternately. The entire system has been implemented based on Zynq FPGA evaluation board. The design has been tested on two MRI images and the results are compared with the Matlab to determine the efficiency of the proposed system. The proposed hardware system has achieved an overall good accuracy compared to Matlab where it ranged between 90.00% and 99.48%

Fast and efficient FPGA implementation of connected operators

International audienceThe Connected Component Tree (CCT)-based operators play a central role in the development of new algorithms related to image processing applications such as pattern recognition, video-surveillance or motion extraction. The CCT construction, being a time consuming task (about 80% of the application time), these applications remain far-off mobile embedded systems. This paper presents its efficient FPGA implementation suited for embedded systems. Three main contributions are discussed: an efficient data structure proposal adapted to representing the CCT in embedded systems, a memory organization suitable for FPGA implementation by using on-chip memory and a customizable hardware accelerator architecture for CCT-based applications

New Proposed Methodologies for Detection of Eye Diseases in Human Beings using HDL, Modelsim Matlab, Python & Tensor Flow w.r.t. the Bio-Medical Image Processing Point of View

In this research paper, the proposed methodologies for glaucoma detection are presented using different hardware & software tools

Image Based Congestion Detection Algorithms And Its Real Time Implementation

In recent years, intelligent traffic management have included many new fields and features. One of the important fields which directly affect our life is the traffic congestion alert system i.e. a complete system which is able to detect congestion and alert concerned parties to save time, fuel and man power. Recent methods in congestion detection need prior knowledge about the road or several minutes are taken to produce results or a huge infrastructure is needed to implement the system, even then, not in real time. Most of the current studies in image processing are not reliable for real implementation because they either lack accuracy or do not work in real time. The proposed system aims to find a new congestion detection method that has high accuracy and having real time processing time, also it aims to demonstrate the transmit/receive process for image transmission using Software Defined Radio. The proposed system offers a complete detection and alert network that captures an image of the road situation, determine whether the road is congested or clear and finally report the results wirelessly to the traffic management bodies to take action and inform people to avoid the congested areas in real time. The proposed system uses a fast and reliable method to detect traffic congestions. The methodology includes vehicle detection by using backlight pairing feature algorithm and modified Watershed algorithm. The results returned by the algorithms are transmitted and received wirelessly using the SFFSDR platform, including the use of RF, FPGA, and DSP modules for variable distances. The system shows an accuracy of detection up to 98-98.8% with time consumption of up to 3 seconds which make it feasible for real time implementation. The wireless system has been tested using different distances between SDR antennas. The received power, bit loss percentage and PSNR for the received image have been obtained, results shows a 35dB PSNR for normal distance between SDR antennas (20cm) and 7dB for 150cm, while bits are totally lost when reaching 200cm

Analysis & Detection of Primary & Secondary Glaucoma – A Brief Survey

This paper gives a brief review about the glaucoma eye disease detection so that any person who is working on the similar disease would get a small idea so that he / she can get some idea about the disease in the human eye. In fact to say, the paper can be thought of as an introductory paper about the Glaucoma. A number of researchers have worked on the static & dynamic mobile WSNs till date (both at the simulation level & at the hardware implementation levels). To start with, 100’s of research papers were collected from various sources, studied @ length & breadth and a brief review of the eye disease issues was being made & presented here in a nutshell. In the sense, the recent works done by various authors across the globe is being presented here in this context so that this review article serves as the base for any researcher who is working in the field of ophthalmology

Real-Time Vision System for License Plate Detection and Recognition on FPGA

Rapid development of the Field Programmable Gate Array (FPGA) offers an alternative way to provide acceleration for computationally intensive tasks such as digital signal and image processing. Its ability to perform parallel processing shows the potential in implementing a high speed vision system. Out of numerous applications of computer vision, this paper focuses on the hardware implementation of one that is commercially known as Automatic Number Plate Recognition (ANPR).Morphological operations and Optical Character Recognition (OCR) algorithms have been implemented on a Xilinx Zynq-7000 All-Programmable SoC to realize the functions of an ANPR system. Test results have shown that the designed and implemented processing pipeline that consumed 63 % of the logic resources is capable of delivering the results with relatively low error rate. Most importantly, the computation time satisfies the real-time requirement for many ANPR applications

Implementation of watershed based image segmentation algorithm in FPGA

The watershed algorithm is a commonly used method of solving the image segmentation problem. However, of the many variants of the watershed algorithm not all are equally well suited for hardware implementation. Different algorithms are studied and the watershed algorithm based on connected components is selected for the implementation, as it exhibits least computational complexity, good segmentation quality and can be implemented in the FPGA. It has simplified memory access compared to all other watershed based image segmentation algorithms. This thesis proposes a new hardware implementation of the selected watershed algorithm. The main aim of the thesis is to implement image segmentation algorithm in a FPGA which requires minimum hardware resources, low execution time and is suitable for use in real time applications. A pipelined architecture of algorithm is designed, implemented in VHDL and synthesized for Xilinx Virtex-4 FPGA. In the implementation, image is loaded to external memory and algorithm is repeatedly applied to the image. To overcome the problem of over-segmentation, pre-processing step is used before the segmentation and implemented in the pipelined architecture. The pipelined architecture of pre-processing stage can be operated at up to 228 MHz. The computation time for a 512 x 512 image is about 35 to 45 ms using one pipelined segmentation unit. A proposal of parallel architecture is discussed which uses multiple segmentation units and is fast enough for the real time applications. The implemented and proposed architectures are excellent candidates to use for different applications where high speed performance is needed

The Impact of Different Image Thresholding based Mammogram Image Segmentation- A Review

Images are examined and discretized numerical capacities. The goal of computerized image processing is to enhance the nature of pictorial data and to encourage programmed machine elucidation. A computerized imaging framework ought to have fundamental segments for picture procurement, exceptional equipment for encouraging picture applications, and a tremendous measure of memory for capacity and info/yield gadgets. Picture segmentation is the field broadly scrutinized particularly in numerous restorative applications and still offers different difficulties for the specialists. Segmentation is a critical errand to recognize districts suspicious of tumor in computerized mammograms. Every last picture have distinctive sorts of edges and diverse levels of limits. In picture transforming, the most regularly utilized strategy as a part of extricating articles from a picture is "thresholding". Thresholding is a prevalent device for picture segmentation for its straightforwardness, particularly in the fields where ongoing handling is required