Effect of Molarity on the structural and optical properties of ZnO thin films deposit by CSP

ABSTRACT ZnO thin films have been prepared by chemical spray pyrolysis technique CSP). XRD pattern reveals that the preferred orientation was varied with concentration, topography analysis was done by AFM micrograph which confirm the existence of nonstructural films. The optical properties was done by recorded the transmittane and absorbance which were affected by an increase in concentration. The values of optical energy gap obtained from Tauc relation were 3.17, 3.18 and 3.19 eV for 0.05, 0.1 and 0.5 M respectively. Urbach energy confirms the decrease in band tail as the concentration increase

Thermal image segmentation based on density slicing of color histogram of images

Thermal imaging has been recently used as a new approach for human biometrics. The formation of thermal image is purely based on the heat distribution of an object. It brings some difficulties to image segmentation due to its over centralized intensity distribution and low intensity contrast. Our approach uses color slicing segmentation method to characterize the texture information using various color models. The experimental results of present study shows the color slicing technique can make good effect on the segmentation of tumor structure. We have found that segmenting these images can be made easier by using RGB, HSV, YCbCr color models by Color slicing method. We have used many Statistical operations (such as contrast, variation …) to evaluate our segmentation results

Enhancement of Underwater Image using Fuzzy Histogram Equalization

Image enhancement is a process of improving the quality of image by improving its feature. The underwater images suffer from low contrast and resolution due to scattering of light and poor visibility conditions. In this paper we proposed an image enhancement technique to enhance the quality of underwater images. The proposed technique comprises a combination of classical contrast enhancement techniques and fuzzyhistogram equalization techniques. For comparing the performance, some statistics parameter is used. The proposed technique comprises a combination of classical contrast enhancement techniques and fuzzy-histogram equalization techniques. Experiment results demonstrate the effectiveness of fuzzy logic techniques to enhance the quality of the underwater images

Diagnosis of Breast Cancer by Optical Image Analysis

We consider the process of object detection, recognition and classification in digital optical images of human breast cells with the aim of differentiating between normal and abnormal (cancerous) cells. The work is based on research into the development of a breast cancer screening system that can be used by cytologists to differentiate between benign and malignant types using images that are typical of those currently interpreted by cytologists world-wide. The approach considered is based on feature vectors which are of two types. We consider statistical features such as the mode, median, mean, and standard deviation and features composed of Euclidian geometric parameters such as the object perimeter, area and infill coefficient. All components of the feature vectors are computed to reflect the statistical characteristics and the geometric structure of the imaged cells. The recognition process includes a segmentation algorithm based on an adaptive imaging threshold procedure that is sensitive to local ranges in pixel intensity (minimum-maximum values). Decision criteria are based on the application of Fuzzy Logic and Membership Function theory. In particular, we present a technique for the creation and extraction of data to construct the Membership Function