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Color image segmentation is an emerging topic in current image processing research. There exist different techniques for the same. Region based approach like watershed algorithm is one of them. But, watershed approach normally results in problems like over segmentation, noise, etc. In this paper, an efficient approach for the color image segmentation is proposed. Here, the input image is converted...
This Diabetic retinopathy poses a heavy threat to vision. Digital colored structure images can be used for distinguishing the eye structure. They produce a high-quality record of the structured image which is useful for detecting DR as primitive signs. Exudates are considered one in every of the earliest signs of DR. Ant colony optimization technique and Gabor filter approach is used for segmenting...
Diabetic Myonecrosis is an unusual and underestimated disorder that occurs in patients who show laxity in controlling diabetes. The main objective of this research work is to give easy analysis of the anomalies underlying due to DM using various Imaging technologies. In this process an improved hybrid image processing model has been developed by combining pre-processing method Hybrid Morphological...
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...
Segmentation process of an Image, represents meaningful way for further analysis and use in medical imaging, remote sensing and military objects detection. Due to poor resolution, segmentation become complex especially is an image is blurred or mixed pixels. Active contour technique is popular to get smooth curve around the boundary of 2D images but due to image gradient this techniques is unable...
Satellite color images carry a vast amount of information which needs an efficient image segmentation method to analyze. Because of its simplicity and low complexity, K-Means algorithm is frequently adopted for color image segmentation. But, usually the results of K-Means algorithm suffers from noises and hence over segmentation. This is due to the reasons that K-Means works on the basis of random...
Sign Language is the main communicating tool for hearing impaired and mute people, and to ensure an independent life for them, the automatic interpretation of sign language is an extensive research area. With the use of image processing and artificial intelligence, many techniques and algorithms have been developed in this area. Every sign language recognition system is trained for recognizing the...
This paper presents a new region growing based color image segmentation technique with the use of RGB channels. The seed pixel selection and region growing phases are based on 8-neighbour connectivity similarity measurement. The region growing process based on intensity measurement between the seed pixel and 8-neighbour pixels of seed pixel. Region growing is applied to Red channel; Green channel...
The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal thresholds...
In most of the studies related to human computer interaction like face detection, human detection, face recognition and emotion detection in the color image or videos, skin color was used as a cue or a feature. Because it handles some well defined problems such as pose, orientation and partial occlusion and varying illumination conditions. In spite of advantages of using skin as cue for various human...
Biomedical analysis is a highly challenging area where lot of research activities is going on. Many automated biomedical image processing procedures have cell segmentation as its first step. Manual methods for this purpose are imprecise, tedious and highly subjective. Hence, novel automated methods are necessary. Analysis of cells includes segmenting the cells as well as computing the area of cell...
In this paper we have proposed Noise Induced HSI model based noisy and blurred colour image segmentation technique. This approach uses additive noise to suppress the effect of internal noise present in an image for proper detection of objects from such images. In this algorithm we decompose a given image in Hue, Saturation and Intensity (HSI) components and then apply processing on intensity component...
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