Today's traffic congestion in the big city is a serious problem, as it causes lot of environmental pollution and difficulty transportation, which leads to difficult daily life for human beings addition material losses. In this work smart light controller was designed using fuzzy logic image processing with MATLAB, control movement two ways, aided by camera auto sensors. The Fuzzy has inputs six...

Brain tumor detection is one of the most critical tasks in the field of medical image processing. Various studies reveal that the existing methods have not considered the images of poor quality like images with high noise and low brightness due to significant image processing difficulty, which can leads to error in assessment. In an image, noise may creep in at various stages such as at the tim...

Image filtering is a technique to preserve important signal elements such as edges, smoothing the details of the image to make images appear clear and sharpener. Among all the non linear concepts to suppress Gaussian noise,the fuzzy logic based approaches are important as they are cabable of reasoning with vague and uncertain informations. In this study, we present a new method for the noise re...

This work addresses the problem of signal separation for 2-Dimensional spaces. Instead of resorting to statistical properties of the signals, this work treats the problem as one of image segmentation. Variants of known fuzzy classifiers are studied and compared with existing techniques, as the Unsupervised Maximum Likelihood (MLU) classifier or the watershed technique. The goal is the separatio...

potato image segmentation is an important part of image-based potato defect detection. this paper presents a robust potato color image segmentation through a combination of a fuzzy rule based system, an image thresholding based on genetic algorithm (ga) optimization and morphological operators. the proposed potato color image segmentation is robust against variation of background, distance and ...

In this paper we will show a way how to detect edges in digital images. Edge detection is a fundamental part of many algorithms, both in image processing and in video processing. Therefore it is important that the algorithm is efficient and, if possible, fast to carry out. The fuzzy set theory based approach on edge detection is good for use when we need to make some kind of image segmentation,...

1106 | P a g e Abstract--Image processing plays an important role in medical field because of its capability. Particularly, image segmentation offer several guides in medical field for analyzing the captured image. Usually, the medical images are captured via different medical image acquisition techniques. The captured image may be affected by noise because of some faults in the capturing devis...

Breast cancer is one of the leading causes of death among women. Mammography remains today the best technology to detect breast cancer, early and efficiently, to distinguish between benign and malignant diseases. Several techniques in image processing and analysis have been developed to address this problem. In this paper, we propose a new solution to the problem of computer aided detection and...

Lung lesion segmentation refers to the process of partitioning an image into mutually exclusive regions. This study gives a new approach to K-means clustering technique (K-CT) integrated with Fuzzy C-means algorithm for lung segmentation. In the study, large number of images with various types of segmentation was selected and examined. It is followed by thresholding and level set segmentation s...