AgroSearch
Autor: | Sunil More, Mininath K. Nighot |
---|---|
Rok vydání: | 2016 |
Předmět: |
business.industry
Computer science Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION k-means clustering Image processing 04 agricultural and veterinary sciences 02 engineering and technology Machine learning computer.software_genre Support vector machine Search engine Feature (computer vision) 040103 agronomy & agriculture 0202 electrical engineering electronic engineering information engineering 0401 agriculture forestry and fisheries Web application 020201 artificial intelligence & image processing Artificial intelligence Data mining business Cluster analysis computer |
Zdroj: | Proceedings of the Second International Conference on Information and Communication Technology for Competitive Strategies. |
DOI: | 10.1145/2905055.2905102 |
Popis: | Uneven climate change demands improved and modern methods for agriculture domain. Also increased demand for food to accommodate global population, farmers try to multiply food production. Automation and intelligent decision system helps to accomplish this mission. AgroSearch is web based search tool help farmers to identify diseases and pests for pomegranate as well as provides remedy. User gives the query in the form of text, image and visual image click and gets results like search engine. It follows image preprocessing, feature extraction, training and testing respectively. Features extracted from images are color, color coherence vector and morphology. Clustering is done by applying K-Means algorithm. Finally classification of image using Multi-class Support Vector Machine into one of the class. Morphology feature gives better results. Accuracy of system is 84% and validated experimentally. |
Databáze: | OpenAIRE |
Externí odkaz: |
Pro tento záznam nejsou dostupné žádné jednotky.