scholarly journals PLANT LEAF IMAGE RECOGNITION SYSTEM

2021 ◽  
Vol 1 (1) ◽  
pp. 35-44
Author(s):  
Gaurav Kulkarni ◽  
◽  
Chandrashekhar Kumbhar
Keyword(s):  
Image Processing ◽  
Object Recognition ◽  
Image Recognition ◽  
Recognition System ◽  
Vital Role ◽  
Rare Plant ◽  
Plant Recognition ◽  
Identification Techniques ◽  
Leaf Image ◽  
End Results

Plants play a vital role in our day-to-day life. Hence, a good understanding of plants is needed to help in identifying new or rare plant species. Such identification will in turn improve the drug industry, balance the ecosystem as well as the agricultural productivity and sustainability. We often come across various plants with different variety of leaves and flowers every single day. We try to recognize it, but we fail. So we need some system which can tell us about the leaf/flower instantly. So, to solve such problems, we introduce a plant recognition system (PRS) which tells you the details about a leaf by just uploading the image of the leaf. For this system, we use image processing and some identification techniques which can recognize the leaf by its structure, colour, shape etc and fetch the details about it and provide the details of it to the user. This paper gives a understanding about the different methods used under image processing and various methods and algorithm used to identify that leaf in a short and simple way. Object recognition and detection are techniques with similar end results and implementation approaches. Therefore, it requires heavy pre-processing and implements various processes to obtain the end results.

scholarly journals Plant Diseases Recognition Based on Image Processing Technology

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Guiling Sun ◽  
Xinglong Jia ◽  
Tianyu Geng
Keyword(s):  
Image Processing ◽  
Image Segmentation ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Image Recognition ◽  
Color Image ◽  
Regional Growth ◽  
Recognition System ◽  
Plant Diseases ◽  
Image Feature

A new image recognition system based on multiple linear regression is proposed. Particularly, there are a number of innovations in image segmentation and recognition system. In image segmentation, an improved histogram segmentation method which can calculate threshold automatically and accurately is proposed. Meanwhile, the regional growth method and true color image processing are combined with this system to improve the accuracy and intelligence. While creating the recognition system, multiple linear regression and image feature extraction are utilized. After evaluating the results of different image training libraries, the system is proved to have effective image recognition ability, high precision, and reliability.

Implementation of Leaf Image Recognition System Based on LBP and B/S Framework

2015 ◽  
pp. 661-670
Author(s):  
Sen Zhao ◽  
Xiao-Ping Zhang ◽  
Li Shang ◽  
Zhi-Kai Huang ◽  
Hao-Dong Zhu ◽  
...  
Keyword(s):  
Image Recognition ◽  
Recognition System ◽  
Leaf Image

scholarly journals Segmentation and Classification of Beatboxing Acoustic Voice Tract Variations in MRI through Image Processing Technique

2021 ◽  
Author(s):  
Anurag Sinha ◽  
Harsh soni
Keyword(s):  
Image Processing ◽  
Clustering Algorithms ◽  
Histogram Equalization ◽  
Recognition System ◽  
Processing Technique ◽  
Vital Role ◽  
Machine Learning Techniques ◽  
Image Processing Technique ◽  
Sound Recognition ◽  
Vocal Art

Human beatboxing is a vocal art making use of speech organs to produce vocal drum sounds and imitate musical instruments. Beatbox sound classification is a current challenge that can be used for automatic database annotation and music-information retrieval. In this study, a large-vocabulary humanbeatbox sound recognition system was developed with an adaptation of Kaldi toolbox, a widely-used tool for automatic speech recognition. The corpus consisted of eighty boxemes, which were recorded repeatedly by two beatboxers. The sounds were annotated and transcribed to the system by means of a beatbox specific morphographic writing system (Vocal Grammatics). The image processing techniques plays vital role on image Acquisition, image pre-processing, Clustering, Segmentation and Classification techniques with different kind of images such as Fruits, Medical, Vehicle and Digital text images etc. In this study the various images to remove unwanted noise and performs enhancement techniques such as contrast limited adaptive histogram equalization, Laplacian and Harr filtering, unsharp masking, sharpening, high boost filtering and color models then the Clustering algorithms are useful for data logically and extract pattern analysis, grouping, decision-making, and machine-learning techniques and Segment the regions using binary, K-means and OTSU segmentation algorithm. It Classifying the images with the help of SVM and K-Nearest Neighbour(KNN) Classifier to produce good results for those images.

A Review of 3D Aircraft Image Recognition Methods

2012 ◽  
Vol 433-440 ◽  
pp. 2794-2801
Author(s):  
Xu Feng Zhu ◽  
Cai Wen Ma
Keyword(s):  
Feature Extraction ◽  
Object Recognition ◽  
Image Recognition ◽  
Recognition System ◽  
System Model ◽  
3D Object Recognition ◽  
3D Object ◽  
New Methods ◽  
The Future ◽  
2D Images

This paper provides a review of 3D aircraft object recognition methods based on 2D images. First, essentialities and advantages on 3D aircraft image recognition are analyzed. Second, in view of the aircraft image recognition system model, the traits of aircraft images are elaborated, then the methods of aircraft image recognition at every stage are discussed, especial the methods of feature extraction about aircraft image and the feasibilities, which some new methods about 3D object recognition are used to aircraft image recognition, are focused. At last, some issues about aircraft image recognition which should be further studied in the future are proposed.

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