Identifikasi Karakteristik Citra Berdasarkan pada Nilai Entropi dan Kontras

Abstract Determining the object boundaries in an image is a necessary process, to identify the boundaries of an object with other objects as well as to define an object in the image. The acquired image is not always in good condition, on the other hand there is a lot of noise and blur. Various edge detection methods have been developed by providing noise parameters to reduce noise, and adding a blur parameter but because these parameters apply to the entire image, but lossing some edges due to these parameters. This study aims to identify the characteristics of the image region, whether the region condition is noise, blurry or otherwise sharp (clear). The step is done by dividing the four regions from the image size, then calculating the entropy value and contrast value of each formed region. The test results show that changes in region size can produce different characteristics, this is indicated by entropy and contrast values ​​of each formed region. Thus it can be concluded that entropy and contrast can be used as a way to identify image characteristics, and dividing the image into regions provides more detailed image characteristics. &nbsp

SEGMENTASI KARAKTER TULISAN TANGAN ONLINE MENGGUNAKAN FILTER IIR

Segmentasi karakter merupakan proses yang sangat penting dalam analisa dan pengenalan karakter tulisan tangan. Paper ini adalah mengembangkan suatu metode segmentasi yang dapat menghasilkan segmen karakter tulisan tangan online sesuai dengan segmentasi acuan. Beberapa algoritma segmentasi telah dikembangkan. Sebagian menggunakan pendekatan wavelet dan sebagian lagi menggunakan pendekatan filter. Karakteristik data yang digunakan pada kedua pendekatan tersebut adalah kecepatan linear. Penggunaan karakteristik ini masih menghasilkan derau yang tinggi, sehingga mempersulit proses segmentasi. Hal ini disebabkan karena adanya perbedaan kecepatan menulis dan kecepatan sampling. Sulitnya proses segmentasi terjadi karena adanya lokal maksimum dan minimum yang bukan sebenarnya. Akibatnya, titik potong segmentasi menjadi tidak tepat. Secara keseluruhan proses segmentasi menjadi tidak akurat dan tidak sesuai dengan segmen acuan. Untuk menghilangkan atau memfilter derau tersebut digunakan filter smoothing IIR (infinite impulse response filters). Filter ini memiliki kemampuan yang baik dalam menghilangkan atau memfilter derau. Penghilangan derau pada data karakter tulisan tangan online ini untuk mempermudah proses segmentasi. Selain itu, penggunaan filter IIR ini dapat meningkatkan akurasi posisi pemotongan segmen. Paper ini menggunakan 52 data karakter tulisan tangan online yang terdiri dari dua set data karakter a-z. Hasil eksperimen yang diperoleh menunjukan bahwa filter IIR menghasilkan proses smoothing yang baik. Hal ini dibuktikan dengan sedikitnya lokal maksimum dan minimum yang dihasilkan sehingga memudahkan melakukan pemotongan pada titik segmen dan diperoleh ketepatan jumlah segmen dan posisi pemotongan segmen

Evolution-Operator-Based Single-Step Method for Image Processing

This work proposes an evolution-operator-based single-time-step method for image and signal processing. The key component of the proposed method is a local spectral evolution kernel (LSEK) that analytically integrates a class of evolution partial differential equations (PDEs). From the point of view PDEs, the LSEK provides the analytical solution in a single time step, and is of spectral accuracy, free of instability constraint. From the point of image/signal processing, the LSEK gives rise to a family of lowpass filters. These filters contain controllable time delay and amplitude scaling. The new evolution operator-based method is constructed by pointwise adaptation of anisotropy to the coefficients of the LSEK. The Perona-Malik-type of anisotropic diffusion schemes is incorporated in the LSEK for image denoising. A forward-backward diffusion process is adopted to the LSEK for image deblurring or sharpening. A coupled PDE system is modified for image edge detection. The resulting image edge is utilized for image enhancement. Extensive computer experiments are carried out to demonstrate the performance of the proposed method. The major advantages of the proposed method are its single-step solution and readiness for multidimensional data analysis

Edge detection using neural network arbitration

A human observer is able to recognise and describe most parts of an object by its contour, if this is properly traced and reflects the shape of the object itself. With a machine vision system this recognition task has been approached using a similar technique. This prompted the development of many diverse edge detection algorithms. The work described in this thesis is based on the visual observation that edge maps produced by different algorithms, as the image degrades. Display different properties of the original image. Our proposed objective is to try and improve the edge map through the arbitration between edge maps produced by diverse (in nature, approach and performance) edge detection algorithms. As image processing tools are repetitively applied to similar images we believe the objective can be achieved by a learning process based on sample images. It is shown that such an approach is feasible, using an artificial neural network to perform the arbitration. This is taught from sets extracted from sample images. The arbitration system is implemented upon a parallel processing platform. The performance of the system is presented through examples of diverse types of image. Comparisons with a neural network edge detector (also developed within this thesis) and conventional edge detectors show that the proposed system presents significant advantages

Edge detection using neural network arbitration

A human observer is able to recognise and describe most parts of an object by its contour, if this is properly traced and reflects the shape of the object itself. With a machine vision system this recognition task has been approached using a similar technique. This prompted the development of many diverse edge detection algorithms. The work described in this thesis is based on the visual observation that edge maps produced by different algorithms, as the image degrades. Display different properties of the original image. Our proposed objective is to try and improve the edge map through the arbitration between edge maps produced by diverse (in nature, approach and performance) edge detection algorithms. As image processing tools are repetitively applied to similar images we believe the objective can be achieved by a learning process based on sample images. It is shown that such an approach is feasible, using an artificial neural network to perform the arbitration. This is taught from sets extracted from sample images. The arbitration system is implemented upon a parallel processing platform. The performance of the system is presented through examples of diverse types of image. Comparisons with a neural network edge detector (also developed within this thesis) and conventional edge detectors show that the proposed system presents significant advantages

Contributions à la segmentation d'image : phase locale et modèles statistiques

Ce document presente une synthèse de mes travaux apres these, principalement sur la problematique de la segmentation d’images

Detecção e agrupamento de contornos

A detecção de contornos a partir de imagens digitais é um procedimento do qual resulta informação essencial para muitos algoritmos de visão por computador. A natureza das imagens digitais bidimensionais: a sua relativamente baixa resolução; a amostragem espacial e em amplitude; a presença de ruído; a falta de informação em profundidade; as oclusões, etc., e a importância dos contornos como informação básica para muitos outros algoritmos a montante, fazem com que a detecção de contornos seja um problema apenas parcialmente resolvido, com múltiplas abordagens e dando origem desde há algumas décadas a larga quantidade de publicações. Continua a ser um tema actual de investigação como se comprova pela quantidade e qualidade das publicações científicas mais actuais nesta área. A tese discute a detecção de contornos nas suas fases clássicas: a estimação da amplitude do sinal que aponta a presença de um ponto de contorno; a pré-classificação dos pontos da imagem com base nos sinais estimados e o posterior agrupamento dos pontos de contorno individuais em segmentos de curvas de contorno. Propõe-se, nesta tese: um método de projecto de estimadores de presença de pontos de contorno baseado na utilização de equações integrais de Fredholm; um classificador não-linear que utiliza informação de pontos vizinhos para a tomada de decisão, e uma metodologia de agrupamento de pontos de contorno com crescimento iterativo com uma função de custo com suporte local. A metodologia de extracção das propriedades baseada na equação integral de Fredholm de primeira ordem permite uma análise unificadora de vários métodos previamente propostos na literatura sobre o assunto. O procedimento de classificação dos pontos de contorno baseia-se na análise das sequências ordenadas das amplitudes do gradiente na vizinhança do ponto de contorno. O procedimento é estudado com base nas funções densidade de distribuição das estatísticas ordenadas dos pontos de contorno vizinhos e na assunção de que os pontos de um mesmo contorno possuem distribuições ordenadas similares. A fase final da detecção de contornos é realizada com um procedimento de agrupamento de contornos em que se constrói uma hipótese de vizinhança para eventual crescimento do contorno e em que se estima o melhor ponto para agregação ao contorno. Os resultados experimentais para os métodos propostos são apresentados e analisados com imagens reais e sintéticas

Effects of Malformed or Absent Valves to Lymphatic Fluid Transport and Lymphedema in Vivo in Mice

Lymph is primarily composed of fluid and proteins from the blood circulatory system that drain into the space surrounding cells, interstitial space. From the interstitial space, the fluid enters and circulates in the lymphatic system until it is delivered into the venous system. In contrast to the blood circulatory system, the lymphatic system lacks a central pumping organ dictating the predominant driving pressure and velocity of lymph. Transport of lymph via capillaries, pre-collecting and collecting lymphatic vessels relies on the synergy between pressure gradients, local tissue motion, valves and lymphatic vessel contractility. The direction of lymph transport is regulated by bicuspid valves distributed throughout pre-collecting and collecting lymphatic vessels. Effective transport of lymph into the venous system is of prime importance. Disruption of lymph transport, because of impaired lymphatic function, reduced numbers of vessels or valvular insufficiencies can have severe health consequences, including lymphedema for which current clinical therapies are not curative. The lymphatic valves are usually bicuspid, however, congenital malformations in the valve such as single leaflet valve formation and arrested lymphatic valve development are observed and can cause lymphedema. Here we employ 4-week-old mice to study the effects of valves and malformed valves on lymph transport shedding light into some of the potentially underlying consequences of lymphedema. Polyethylene glycol (PEG) coated latex particles were injected into the inguinal lymph node of anesthetized mice. Particle displacement measurements through efferent lymphatic vessels yielded velocity, wall shear stress, vorticity and strain of the efferent lymph flow field carrying lymph from subdermal inguinal lymph nodes. Lymphatic vessel endothelial Prox1 green fluorescent protein (GFP) marker enabled the detection of lymphatic vessel walls and valves. Flow field, flow velocity, flow rate, velocity profiles, wall shear stress, vorticity and strain values were compared in regions downstream of normal and malformed valves in two wild type mice. A Clec2-deficient mouse, which experiences lymphatic development defects and is used as a lymphedema model, was employed to further elucidate the lymphatic valves on transport. The absence of centralized pumping yields highly variable lymphatic flow cycles varying from one to fifteen seconds. The presence of lymphatic valves introduces boundary conditions that yield spatial and temporal flow gradients increasing the degree of complexity of lymph transport. The valves dictate the trajectory of the particles and promote the formation of recirculation zones. Even in the presence of valves, lymph flow commonly reverses. Congenital defects like a single leaflet valve lowers the lymph flow efficiency and promotes higher wall shear stress regions. Furthermore, the absence of functional valves in the Clec2-deficient mouse not displaying lymphedema yielded lymph flow lacking the pulsatility that characterizes normal lymphatic flow