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Tamil Selvan, K. S.
- A Hybrid Method for the Classification of Paddy Varieties Based on Image Segmentation
Authors
1 Velalar College of Engineering and Technology, IN
Source
Digital Image Processing, Vol 7, No 4 (2015), Pagination: 112-115Abstract
In Seed Processing Plant, different paddy varieties are identified and classified manually by visual inspection which is a tedious and less accuracy process. To overcome this, we developed an automated system for identifying and classifying the five different varieties such as ADT-38, ADT-39, ADT-43, ASD-16, and TKM-9 based on their morphological features. In this paper, three phases are involved. In First Phase, Image of paddy seeds are acquired by a digital camera, which is collected from seed unit and the acquired image is stored in JPEG format. The stored image is given to wiener filter for Image pre-processing such as edge detection, image denoising and image enhancement. In Second Phase, Image Segmentation is performed using Dual Tree Complex Wavelet Transform (DTCWT). In Third Phase, from segmented image features are extracted and given to Neural Network to classify the paddy varieties according to the extracted color features, morphological features and shape factors of each paddy grain.Keywords
ADT-43, ADT-39, ADT-38, ASD-16, TKM-9, DT-CWT, Morphological Features, Seed Processing Unit.
- Non-Invasive Deep Brain Stimulation Based on Segmentation Process
Authors
1 Velalar College of Engineering and Technology, Erode, IN
Source
Digital Image Processing, Vol 7, No 4 (2015), Pagination: 116-119Abstract
Due to increase of aging population and increase of movement disorder patients there is a need of reducing the disorder by considering various methods and reduction of overall cost of the treatment method. Recently movement disorders are treated in many ways but it causes some side effects such as stroke occurrence, spinal cord problems and it is highly economical. To minimize the neurosurgical intervention of human, a noninvasive deep brain stimulation method is proposed in which the force feedback signal stimulates the nerve of the deep brain. In this proposed technique, minimum numbers of nerves which are correlated with hand and legs has been identified for stimulating the deep brain by DTCWT and if the nerves attain force feedback signal directly in the form of non-invasive type the patient get recovered without any side effects and the stimulation mechanism is done by the doctors.