Brain tumor extraction in magnetic resonance imaging (MRI) has becoming an emergent research
are... more Brain tumor extraction in magnetic resonance imaging (MRI) has becoming an emergent research area in the field of medical imaging system. Extraction involves detection, localization, tracking, enhancement and recognition of the tumor from the MR brain images. Brain tumor extraction helps in finding the exact size and location of tumor. The watershed transform is a popular and has interesting properties that make it useful for many image segmentation applications. The intuitive description of this transform is quite simple, can be parallelized and always produces a complete division of the medical images. One of the important drawbacks associated to the watershed transform is the over segmentation that commonly results in brain images. We present an improvement to the watershed transform in this paper for the extraction of brain tumor based on segmentation and morphological operator. The tumor may be benign, pre-malignant or malignant and it needs medical support for further classification.
Vehicle License plate extraction is one of the most important applications of intelligent transpo... more Vehicle License plate extraction is one of the most important applications of intelligent transportation systems. Extraction involves detection, localization, tracking, enhancement and recognition of the license plate from the vehicle images. However variation of text due to difference in size, style, orientation, alignment, low image contrast and complex background make the problem of automatic license plate extraction extremely challenging. Text extraction requires binarization which leads to loss of significant information contained in gray scale images. The images may contain noise and have complex structure which makes the extraction more difficult. Hence extracting the license plate in a vehicle image is considered to be the most crucial step of an intelligent transport system. This paper mainly deals with segmentation and extraction of license plate in Indian traffic conditions based on mathematical morphology. Proposed method aims at identifying region of interest by performing a sequence of directional segmentation and morphological processing. The proposed method is tested on large database consisting of 150 images taken in different conditions. The algorithm could detect the license plate in 146 images with success rate of 97.3%.
Brain tumor extraction in magnetic resonance imaging (MRI) has becoming an emergent research
are... more Brain tumor extraction in magnetic resonance imaging (MRI) has becoming an emergent research area in the field of medical imaging system. Extraction involves detection, localization, tracking, enhancement and recognition of the tumor from the MR brain images. Brain tumor extraction helps in finding the exact size and location of tumor. The watershed transform is a popular and has interesting properties that make it useful for many image segmentation applications. The intuitive description of this transform is quite simple, can be parallelized and always produces a complete division of the medical images. One of the important drawbacks associated to the watershed transform is the over segmentation that commonly results in brain images. We present an improvement to the watershed transform in this paper for the extraction of brain tumor based on segmentation and morphological operator. The tumor may be benign, pre-malignant or malignant and it needs medical support for further classification.
Vehicle License plate extraction is one of the most important applications of intelligent transpo... more Vehicle License plate extraction is one of the most important applications of intelligent transportation systems. Extraction involves detection, localization, tracking, enhancement and recognition of the license plate from the vehicle images. However variation of text due to difference in size, style, orientation, alignment, low image contrast and complex background make the problem of automatic license plate extraction extremely challenging. Text extraction requires binarization which leads to loss of significant information contained in gray scale images. The images may contain noise and have complex structure which makes the extraction more difficult. Hence extracting the license plate in a vehicle image is considered to be the most crucial step of an intelligent transport system. This paper mainly deals with segmentation and extraction of license plate in Indian traffic conditions based on mathematical morphology. Proposed method aims at identifying region of interest by performing a sequence of directional segmentation and morphological processing. The proposed method is tested on large database consisting of 150 images taken in different conditions. The algorithm could detect the license plate in 146 images with success rate of 97.3%.
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Papers by J. Mehena
area in the field of medical imaging system. Extraction involves detection, localization, tracking, enhancement
and recognition of the tumor from the MR brain images. Brain tumor extraction helps in finding the exact size
and location of tumor. The watershed transform is a popular and has interesting properties that make it useful
for many image segmentation applications. The intuitive description of this transform is quite simple, can be
parallelized and always produces a complete division of the medical images. One of the important drawbacks
associated to the watershed transform is the over segmentation that commonly results in brain images. We
present an improvement to the watershed transform in this paper for the extraction of brain tumor based on
segmentation and morphological operator. The tumor may be benign, pre-malignant or malignant and it needs
medical support for further classification.
area in the field of medical imaging system. Extraction involves detection, localization, tracking, enhancement
and recognition of the tumor from the MR brain images. Brain tumor extraction helps in finding the exact size
and location of tumor. The watershed transform is a popular and has interesting properties that make it useful
for many image segmentation applications. The intuitive description of this transform is quite simple, can be
parallelized and always produces a complete division of the medical images. One of the important drawbacks
associated to the watershed transform is the over segmentation that commonly results in brain images. We
present an improvement to the watershed transform in this paper for the extraction of brain tumor based on
segmentation and morphological operator. The tumor may be benign, pre-malignant or malignant and it needs
medical support for further classification.