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Mathematical morphology is widely used in the area of signal and image analysis. It has enormous applications in detection of weak targets, object recognition and feature extraction, edge detection, image enhancement and many more. However, its use has long been hampered by its algorithmic complexity as the size of the structuring element or image grows. With the trend toward larger images and proportionally...
In this paper we present a morphologic edge detector using multidirectional structuring element approach for detecting edges of complex images under noisy condition. The experimental results show that the proposed edge detector has the desirable properties that a good edge detector should have. Comparative study reveals its detection performance exceeds conventional edge detectors and other morphologic...
PET and CT image registration is an important tool of clinical diagnosis of diseases. For PET and CT images, a preprocessing algorithm of medical image registration is proposed in this paper. The algorithm process includes image normalization, CT image adaptive threshold adjustment and automatic extraction of tissues based on morphology, edge detection and statistical analysis theory, and improved...
Edge detection is one of the fundamental issues of digital image, in this paper, mathematical morphology method and several classical edge detection operators are reviewed. This paper provides two methods: Canny operator and mathematical morphology, which summaries relatively good image edge detection methods, and provides a reference for some detection occasions where requires smaller edge width...
A novel morphological edge detection using adaptive weighted morphological operators is presented. The newly introduced operators employ a weighted structuring element and apply multiplication or division in place of addition and subtraction in classical morphological operations. It judges its edge and its direction by morphological operation. If the edge exists, a big weight factor is put; if the...
This paper presents a robust vehicle license plate detection algorithm based on multi-features, including mathematical morphology, rectangle features, edge statistics and characters features. Here we utilize the word ??robust?? to describe the proposed algorithm because it is not only adaptive to variance occasions, such as variance of the illumination, vehicle position, the color, both background...
Combined with human visual characteristics and morphological watershed algorithm, a novel image processing method was proposed for automatic region of interest (ROI) extraction. The color image would be converted into gradient map, then smooth the map using the method of morphological opening and closing operators, last thresholding it. For discriminating the very small regions which are segmented...
Locating the car license plate in an image a car is an important step in car license plate recognition/identification applications. This problem poses many challenges like location of license plate from images taken in poor illumination and bad weather condition; plates that are partly obscured by dirt and images that have low contrast. This paper presents a morphology based method for license plate...
License plate detection plays an important role in license plate recognition (LPR) system. If license plate can be detected exactly, the character segmentation and recognition can be implemented more precisely and efficiently. In our observation, the illumination affects the result of detecting the license plate. The aim of this paper is to extract more than one license plate from an image and to...
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