http://hdl.handle.net/20.500.12228/21 2026-04-08T01:55:25Z 2026-04-08T01:55:25Z Tanveer, Md. Siddiqur Rahman http://hdl.handle.net/20.500.12228/903 2021-09-08T05:01:06Z 2020-09-01T00:00:00Z

A Technique for Assuring Secrecy and Lossless Properties of Digital Image Tanveer, Md. Siddiqur Rahman Due to various disease diagnosis, the volume of medical data is rising fast. Also, for telemedicine, while medical image transmits over the public network, the distortion of pixels may cause erroneous disease diagnosis. Here, encryption of the image by multiple chaos-based schemes along with DNA cryptography can be a safeguard. As chaotic schemes are very sensitive to the initial conditions, a small difference in the initial conditions yields entirely uncorrelated sequences that assure the strength of encryption. To get high randomness, several DNA encoding and computing rules are deployed. This thesis proposes a multi-stage chaotic encryption technique for the medical image through Logistic map along with Lorenz attractor and DNA cryptography, where both schemes possess the most significant value of control parameters. Thus, their consecutive deployment generates colossal chaotic sequences that ensure the robustness of the proposed technique. At first, the usage of the Logistic map with SHA-256 hash value generates a chaotic sequence that converts the plain medical image into a confusing image. Now, this sequence is used to create a confusion key to encrypt this blur image. Later on, to overcome the limitations of DNA computing rules and to get high randomness, encode this blur image and Lorenz attractor based key according to DNA encoding rules. These rules are determined randomly from eight encoding rules. Then, execute DNA operations between encoded blur image and Lorenz key using the four DNA computing rules and these rules are also determined by chaotic logistic sequence. Thus, the ultimate cipher is generated. Then, to approve the potency of the cipher, a randomness test according to NIST, security and statistical analyses and comparisons are performed. This thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, September 2020.; Cataloged from PDF Version of Thesis.; Includes bibliographical references (pages 42-47).

2020-09-01T00:00:00Z Afrin, Rubya http://hdl.handle.net/20.500.12228/902 2021-01-12T21:00:13Z 2020-10-01T00:00:00Z

Automatic Detection and Classification of Diabetic Lesions for Grading Diabetic Retinopathy Using Fuzzy Rule-Based Classification System Afrin, Rubya Diabetic Retinopathy (DR) is a chronic, progressive retinal disease which is the most common cause of legal blindness. The disease is threatening to eyes as it shows no signs of visual abnormality at the initial stage. It gradually decreases patient’s eye-sight and drives into blindness in future. Hence, the early detection of DR is vital to prevent the complete vision loss of diabetes patients. Traditional diagnosing system of DR requires quite trained ophthalmologists for monitoring the retina periodically. Moreover, several physical tests like fluorescein angiography, visual acuity test, and ocular coherence tomography are involved to detect DR which also require a lot of time to process. In this paper, a fuzzy rule-based classification technique is proposed for automatic detection and classification of retinal lesions for grading DR. The proposed technique consists of preprocessing of fundus images, extraction of candidate retinal lesions, formulation of feature set, and classification of DR. In the preprocessing phase, the technique eliminates background noises and extracts optic disc from the retinal fundus image. Four leading lesions; blood vessels, microaneurysms, haemorrhages, and exudates are extracted using different image processing techniques and two textural features; contrast and homogeneity are calculated in the detection phase. Then, these six input features; blood vessels area, microaneurysms count, haemorrhages area, exudates area, contrast and homogeneity are fed to fuzzy if-then rule-based classifier for predicting normal, mild NPDR, moderate NPDR, severe NPDR and PDR stages of DR.. A total of 520 retinal fundus images are collected from four public database; STARE, DIARETDB0, DIARETDB1 and MESSIDOR and the images are successfully classified by the fuzzy rule-based classifier with accuracy up to 92.42%. The sensitivity and specificity of the classifier are 92.44% and 94.29% respectively. The simulation result on publicly standard image datasets exhibits that the intended technique gives promising results in identifying retinal lesions and it has better capability of classifying several stages of DR compared with other existing automatic diagnosing system. This thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, October 2020.; Cataloged from PDF Version of Thesis.; Includes bibliographical references (pages 52-59).

2020-10-01T00:00:00Z Islam, Aminul http://hdl.handle.net/20.500.12228/900 2020-11-11T21:00:17Z 2019-12-01T00:00:00Z

A Study on the Effect of Seam, Color and Boundary Priors on Salient Region Detection Islam, Aminul Being the best creation of almighty Allah, human beings have the ability to analyse a visual scenario. They not only see an image, but can judge the importance of different parts of a visual area. They can easily differentiate a running car from its background, can tell the color of different objects in an image and can focus attention to some important parts of a visible scene. The value of this visual power of human is easily understood if one thinks about these. Achieving this wonderful human quality using machine is one of the most precious goals of today’s scientific researches. With the continuous advancement of imaging technologies, more and more visual data are being collected all over the world. But, a major portion of these data are left unprocessed. Image processing is used to process these types of visual data. For all image processing techniques, the initial goal is to find some target region for extracting information from the image. Saliency detection is the technique of computationally finding important regions of an image. It is usually done using the contrast information present in an image. Seam map is the combination of cumulative summation of energy values from different directions. In this thesis, a combined method is proposed which uses seam importance map along with boundary aware color importance map. Color importance map is the weighted average of different color channels of Lab color space. Some intermediate combinations which are closer to the proposed optimized version but differ in the optimization technique are also presented in this thesis. Several standard benchmark datasets including the famous MSRA 10k and ECSSD datasets are used to evaluate performance of the suggested method. The proposed saliency model has been compared with several state of the art methods for each dataset. The qualitative and quantitative results from those omparisons make things easier to understand. Besides that, comparison with those state of the art techniques and precision recall curves and F-beta values found from the experiments on several datasets prove the superiority of the proposed method. This robust saliency model can improve almost all types of vision related applications including object detection, robotics, medical image analysis, content aware image resizing etc. In this research, the proposed architecture of saliency detection technique has been applied into a simple implementation of pedestrian detection. Its application has significantly improved the result of pedestrian detection in terms of performance and accuracy. This thesis is submitted to the Department of Computer Science and Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, December 2019.; Cataloged from PDF Version of Thesis.; Includes bibliographical references (pages 57-62).

2019-12-01T00:00:00Z Rani, Saptami http://hdl.handle.net/20.500.12228/899 2020-11-11T21:00:16Z 2019-12-01T00:00:00Z

Design and Demonstration of Smartphone-Based Colorimeter Rani, Saptami In this thesis work, smartphone-based colorimeter is designed and practically implemented utilizing the in-built sensors like CMOS camera, flash LED, and high-power processor of the smartphone. The developed totally self-contained colorimeter is low-cost, light-weight, robust, field-portable and easily accessible. It has smart sensing facilities without the requirement of additional optics and external power supply. The device can be applied for real-time and on-site measurements of different types of analytes in the fields of environmental research, biomedical applications, and agriculture, which are completely absent in the currently used conventional bench-top type colorimetric instruments. In the real-world, for most of the colorimetric detection, attributes of color such as wavelength, intensity, saturation, etc. vary simultaneously according to the variation of analytes. The conventional smartphone-based colorimeters are mainly designed to measure the analytes considering the change in color information in only one domain which limits the colorimetric measurement in some specific analytes with a narrow band of detection. In this research, the developed smartphone-based colorimeter can quantify any analytes through multiple nonlinear regression based colorimetric assessment in a wide range of detection considering the variation of color attributes in all significant domains. To demonstrate the smartphone-based colorimeter a 3D optical enclosure is designed and fabricated for ensuring the constant illumination and hence to improve the SNR by isolating the measuring platform from the environmental illumination. Self-referencing is a unique characteristic of the instrument to calculate the color ratio with respect to the colorimetric information of the sample. A customized Android-based smartphone app is developed for the complete functioning of the developed colorimeter. The app is developed with the graphical user interfaces of calibration, assessment of the real-time or previously recorded test samples, save, and share the results of colorimetric measurement for multiple analytes of different colorimetric tests. For the first time, a novel wavelength estimation algorithm is developed to estimate the wavelength information of the reflected light of colorimetric measurement. To justify the performance of the developed colorimeter, three different colorimetric tests are demonstrated in this research named as Rhodamine B concentration quantifier, digital pH meter, and chlorine concentration quantifier using the Xiaomi Redmi Note 4 smartphone. Three different colorimetric characteristics are found for the three samples: only color tone changes significantly with the variation of Rhodamine concentration, the wavelength of color varies significantly with the variation of pH value in water, and color intensity, wavelength, and saturation all vary simultaneously with the variation of chlorine concentration. For all of the three colorimetric tests, the performance of the designed smartphone-based colorimeter is found excellent compared to the conventional colorimeters. The average error of RhB concentration quantifier within the detection range of (0.2-4.0) PPM is 0.95% whereas the chlorine concentration quantifier shows an average error of 1.16% for the detection range of (0.1-8.0) PPM with sensitivity 0.1 PPM. On the other hand, the digital pH meter detects pH value in the range of (4.0-9.0) with an average of 0.0876% detection error. It is noted that the present smartphone-based colorimeter is designed and demonstrated using three analytes but the developed device can be applied to measure any colorimetric analytes by proper calibration using the developed smartphone app. So, the developed martphonebased colorimeter could be a cost effective common platform for the colorimetric measurement of various analytes in different fields of applications. This thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Master of Science in Electrical and Electronic Engineering, December 2019.; Cataloged from PDF Version of Thesis.; Includes bibliographical references (pages 82-88).

2019-12-01T00:00:00Z