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Wing ftp server 6.0.2 crack12/27/2023 Testing of jasmine flower image resized 50 Ã- 50 pixels, 100 Ã- 100 pixels, 150 Ã- 150 pixels yields an accuracy of 84%. The data used in this study are three types of jasmine namely jasmine white (Jasminum sambac), jasmine gambir (Jasminum pubescens), and jasmine japan (Pseuderanthemum reticulatum). While k-Nearest Neighbor method is used to classify the classification of test objects into classes that have neighbouring properties closest to the object of training. Edge detection aims to improve the appearance of the border of a digital image. Edge detection is used to detect the type of flower from the flower shape. There is a jasmine that is yellow and there is a jasmine that is white and purple.The aim of this research is to identify Jasmine flower (Jasminum sp.) based on the shape of the flower image-based using Sobel edge detection and k-Nearest Neighbor. People often wrong in knowing the type of jasmine by just looking at the white color of the jasmine, while not all white flowers including jasmine and not all jasmine flowers have white. Identification of jasmine flower (Jasminum sp.) based on the shape of the flower using sobel edge and k-nearest neighbour Between the Sobel and the Canny edge detection techniques, the experimental result shows that the Canny's technique has better ability to detect points in a digital image where image gray level changes even at slow rate. To develop an iris authentication algorithm for personal identification, this paper examines two edge detection techniques for iris recognition system. Iris is one of the most reliable organ or part of human body which can be used for identification and authentication purpose. Nowadays security and authentication are the major parts of our daily life. From the experimental results obtained by the recognition rate of 91.79%.Įdge detection techniques for iris recognition system Experiments carried out in one phase, identification of the leaf edge, using a rubber plant leaf image 14 are superior and 5 for each type of test images (clones) of the plant. Pattern recognition would detect image as input and compared with other images in a database called templates. Edge detection is using Sobel edge detection. The steps research are started with the identification of the image data acquisition, image processing, image edge detection and identification method template matching. This research was conducted to develop a system that can identify and recognize the type of rubber tree based on the pattern of leaves of the plant. Implementation of sobel method to detect the seed rubber plant leaves
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