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Automatic identification and recognition of medicinal plant species in environments such as forests, mountains and dense regions is necessary to know about their existence. In recent years, plant species recognition is carried out based on the shape, geometry and texture of various plant parts such as leaves, stem, flowers etc. Flower based plant species identification systems are widely used. While...
The detection and matching of logos have widely attention for the document images retrieval projects. In this paper an automatic effective logo matching has been developed and applied to different Arabic documents. The proposed technique based on matching between logos by using two types of significant features. The first is region based feature which represent the global features of an object. This...
The main objective of presenting this context is to identify and verify the quality of the seed for future fertilization in the field of agriculture. This research paper proposes a novel image processing technique that includes two phases depicts an optimized selection of feature extraction and classification algorithm that enhances the quality, exactness of the seed variety and realization of the...
There are countless plant species available globally. To manage massive content, development of a fast and effective categorization methods has turned into a territory of dynamic research. As trees and plants are very important to ecology, accurate Identification and classification becomes necessary. Classification procedure is carried out through number of sub procedures. An identification or Classification...
Immense analysis has been done on optical character recognition (OCR). Numerous works has stated for English, Chinese, Devanagari, Malayalam, Arabic scripts, etc. Segmentation has imp phase in OCR and various articles have been published on different segmentation methods like Thinning, histogram etc for different script during last few years. Generally there is not work done on Overlapped and touching...
Approach of detection of buildings on satellite images is presented in this paper. Actuality of work is shown. Possible areas of the use of the research results are presented. The detection is based on joint use of height, color, shape. The height of the object is determined based on energy minimization within the region. The image is segmented previously. The area of vegetation and the shadows are...
This paper proposes a novel method of recognizing plant leaf image using a combination of venation and contour features. In this method, the shape is cut into pieces under different scales to describe the leaf image in a multiscale way. Both leaf venation and contour features extracted from the cut pieces are utilized to provide comprehensive description under each scale. The performance of the proposed...
This paper proposes a methodology for recognition of plant species by using a set of statistical features obtained from digital leaf images. As the features are sensitive to geometric transformations of the leaf image, a pre processing step is initially performed to make the features invariant to transformations like translation, rotation and scaling. Images are classified to 32 pre-defined classes...
This paper presents a fresh food recognition system that utilizes the feature fusion extracted from food images captured from optical fibers embedded inside a chopping board. We exploit both local and global features including color, SURF and shape for image representation. In addition, we propose cost-based schemes for feature matching and the Borda count method for feature fusion. An experiment...
A new method for mango detection is presented in this paper. This method is based on preprocessing operators on image which includes converting to gray image, finding edges, calculating distances to edges, opening morphology and converting to binary color image. To take advantage of oval shaped mango fruit, we apply Randomized Hough Transform method to detect potential places for mango fruit in input...
Scene recognition is an important research topic in robotics and computer vision. Even though scene recognition is a problem that has been studied in depth, indoor scene categorization has had a slow progress. Indoor scene recognition is a challenging problem due to the severe high intra-class variability, mainly due to the intrinsic variety of objects that may be present, and inter-class similarities...
In this paper, a complete logo detection/ recognition system for document images is proposed. In the proposed system, first, a logo detection method is employed to detect a few regions of interest (logo-patches), which likely contain the logo(s), in a document image. The detection method is based on the piece-wise painting algorithm (PPA) and some probability features along with a decision tree. For...
Artificial touch sensing system for various Human Computer Interaction (HCI) applications is required to be capable of recognizing various parameters viz. object shape, size, texture and surface. However, only identifying object-shapes is not sufficient for object recognition. It is necessary to distinguish the object shapes according to their dimensions or sizes. Thus in the present work object shapes...
Due to the advancement of computing and the power of the new hardware, more economical, it is now feasible to have thousands of images which can be analyzed to allow classification for its shape and/or color. Furthermore, techniques and efficiency of the classification depends on the characteristics to be obtained of images in order to compare and classify them according to their similarity. Some...
We propose a segmentation algorithm for the purposes of large-scale flower species recognition. Our approach is based on identifying potential object regions at the time of detection. We then apply a Laplacian-based segmentation, which is guided by these initially detected regions. More specifically, we show that 1) recognizing parts of the potential object helps the segmentation and makes it more...
For recognizing the objects in the image, the existing image recognition methods only can identify certain kinds of objects in the image recognition field and the recognition rate is also not high. This paper proposes an image recognition method which is based on shape feature and texture feature. This method divides the objects images into two types, foreground images and background images. Then...
Lip is claimed to be a unique organ in human body and hence a candidate for being a biometric. The uniqueness of lip has been proven by the researchers by using color information and shape analysis. These measures of lip are unique for every person. This paper proposes that grayscale lip images constitute local features. The claim has been experimentally established by extracting local features from...
Recognizing characters in a scene helps us obtain useful information. For the purpose, character recognition methods are required to recognize characters of various sizes, various rotation angles and complex layout on complex background. In this paper, we propose a character recognition method using local features having several desirable properties. The novelty of the proposed method is to take into...
In this paper, we propose a road sign detection and recognition algorithm for an embedded application, which requires computationally simple but accurate algorithms. The algorithm is developed by using the Hue Saturation Intensity (HSI) color space to segment the road signs color (red, yellow, blue and white) and the regions of interest (ROI) in order to locate and determine the shape of the road...
The purpose of this paper is to develop an automatic camera phone based multi-view food classifier as part of a food intake assessment system. Food intake assessment is important for obesity management, which has shown significant impacts in public healthcare. Conventional dietary record based food intake assessment methods exhibit insufficient popularity due to their low accuracy and high dependence...
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