in modern agriculture, image processing technique is used for mechanization and intelligent machines instead of humans. one of them is identifying varieties of plants and fruits. identifying plant varieties is important in plant eugenic programs. visual examination of plant leaves and fruits are the common processes for this aim. identification and classification of plants using machine vision ...

Image segmentation refers to the technology to segment the image into different regions with different characteristics and to extract useful objectives, and it is a key step from image processing to image analysis. Based on the comprehensive study of image segmentation technology, this paper analyzes the advantages and disadvantages of the existing fuzzy clustering algorithms; integrates the pa...

Wavelet analysis is a powerful tool withmodern applications as diverse as: image processing, signal processing, data compression, data mining, speech recognition, computer graphics, etc. The aim of this paper is to introduce the concept of atomic decomposition of fuzzy normed linear spaces, which play a key role in the development of fuzzy wavelet theory. Atomic decompositions appeared in appli...

Edge detection is still difficult task in the image processing field. In this paper we implemented fuzzy techniques for detecting edges in the image. This algorithm also works for medical images. In this paper we also explained about Fuzzy inference system, which is more robust to contrast and lighting variations. KeywordsFuzzy, FIS.

Image segmentation is an important research topic in image processing and computer vision community. In this paper, we present a novel segmentation method based on the combination of fuzzy connectedness and adaptive fuzzy C means (AFCM). AFCM handles intensity inhomogeneities problem in magnetic resonance images (MRI) and provides effective seeds for fuzzy connectedness simultaneously. With the...

Image Thresholding is a necessary task in many image processing applications. In this paper we derive fuzzy rules for π-function. We use π-function to fuzzify the original image; this is constructed to locate the intensities of the misclassification regions. Based on information theory, it maximizes the information between image foreground and background. The merit of 1 / 4

Mathematical morphology (MM) offers a wide range of tools for image processing and computer vision. MM was originally conceived for the processing of binary images and later extended to gray-scale morphology. Extensions of classical binary morphology to gray-scale morphology include approaches based on fuzzy set theory that give rise to fuzzy mathematical morphology (FMM). From a mathematical p...

Contrast Stretching is an important part in medical image processing applications. Contrast is the difference between two adjacent pixels. Fuzzy statistical values are analyzed and better results are produced in the spatial domain of the input image. The histogram mapping produces the resultant image with less impulsive noise and smooth nature. The probabilities of gray values are generated and...

Human object extraction from infrared image has broad applications, and has become an active research area in image processing community. Combined with chaos differential evolution (CDE) algorithm and morphological operators, a novel infrared human target extraction method is proposed based on nonextensive fuzzy entropy. Firstly, the image was transformed into a fuzzy domain by fuzzy membership...