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Image segmentation is critical to image processing and pattern recognition, An image segmentation system is proposed for the segmentation of color image based on neural networks. First, we introduce BP Neural network, it has the capacity of parallel computing, distributed saving, self-studying, fault-to-learnt and nonlinear function approximating. So it widely used in image segmentation, but it also...
This paper research the use of computer visual and image information collected preprocessing based on pattern recognition of soybean Nitrogen element detect. When Nitrogen elements of the soybean plant changes, color and texture will be characteristic. By nurturing and collecting samples, This work analyzed the characteristics determine preprocessing, established a preprocessing system model. The...
Image segmentation is very essential and critical to image processing and pattern recognition. It is known that, color image segmentation approaches are based on monochrome segmentation approaches operating in different color spaces. So in this paper, an improved method which uses the FSVM (fuzzy support vector machines) algorithm for color image segmentation in the HSI (hue-saturation-intensity)...
In this paper we propose a coin recognition system using a statistical approach and apply it to the recognition of Jordanian coins. The proposed method depends on two features in the recognition process: the color of the coin, and its area. The recognition process consists of several steps. Firstly, a gray-level image is extracted from the original colored image. The image is then segmented into two...
In this paper, we address the problem of image segmentation using unsupervised clustering method. We implement two nature inspired memetic metaheuristics for segmenting images into regions. First, we use shuffled frog leaping algorithm (SFLA) to locate the optimal clusters for the images. We further use the clonal selection based shuffled frog leaping algorithm (CSSFLA) for segmenting the same images...
Reading of the foreground text is difficult in documents having multi colored complex background. Automatic foreground text separation in such document images is very much essential for smooth reading of the document contents. In this paper we propose a hybrid approach which combines connected component analysis and an unsupervised thresholding for separation of text from the complex background. The...
It is an important work to extract a garment style from garment photo, which can get much valuable information to guide manufacture and design for enterprises. But this research is so difficult that no one can study it successfully so far. This paper proposes a set of computer recognition method based on cluster pattern recognition and silhouette knot points detecting. Firstly, garment photos are...
This paper presents biometric verification experiments based on palm colour information. Feasibility of colour components from several different colour models (RGB, normalized rgb, HSL, YUV, CIE XYZ, CIE LAB and Hunter LAB) for the purpose of biometric recognition was determined. According to the recognition rate, feature vectors based on normalized r and normalized b colour components are selected...
We propose a method to video segmentation via active learning. Shot segmentation is an essential first step to video segmentation. The color histogram-based shot boundary detection algorithm is one of the most reliable variants of histogram-based detection algorithms. It is not unreasonable to assume that the color content does not change rapidly within but across shots. Thus, we present a metric...
In this paper, we present a novel approach to detection of one dimensional bar code images. Our algorithm is particularly designed to recognize bar codes, where the image may be of low resolution, low quality or suffer from substantial blurring, de-focusing, non-uniform illumination, noise and color saturation. The algorithm is accurate, fast, scalable and can be easily adjusted to search for a valid...
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