Region growing-based color image segmentation approaches suffer from expensive computation cost. In order to overcome this issue, a novel region-based color image segmentation method based on P systems is proposed in this paper. A tissue-like P system is designed in such a way that an adaptive selection of target regions is achieved. The proposed method is evaluated on several real-life color i...

Segmentation of adjoining objects in a noisy image is a challenging task in image processing. Natural images often get corrupted by noise during acquisition and transmission. Segmentation of these noisy images does not provide desired results, hence de-noising is required. In this paper, we tried to address a very effective technique called adaptive wavelet thresholding for de-noising, followed...

Adaptive Re-Segmentation Strategies for Accurate Bright Field Cell Tracking

The hippocampus has been known as one of the most important structures referred to as Alzheimer's disease and other neurological disorders. However, segmentation of the hippocampus from MR images is still a challenging task due to its small size, complex shape, low contrast, and discontinuous boundaries. For the accurate and efficient detection of the hippocampus, a new image segmentation metho...

Finding a suitable seeding resolution when using superpixel segmentation methods is usually challenging. Different parts of the image contain different levels of clutter, resulting in an either too dense or too coarse segmentation. Since both possible solutions cause problems with respect to subsequent processing, we propose an edge adaptive seeding for superpixel segmentation methods, generati...

Hand gesture segmentation is a key step for gesture recognition. Based on the construction of a new color space of skin model, a new dynamic-thresholding segmentation approach named Adaptive Threshold Segmentation Algorithm (ATSA) was further developed and segmentation effect evaluation was conducted. Some images of hand gesture were processed by using ATSA and the Fixed Threshold Segmentation ...

This chapter considers the multiple change–point problem for time series, including strongly dependent processes, with an unknown number of change– points. We propose an adaptive method for finding the segmentation, i.e., the sequence of change–points τ with the optimal level of resolution. This optimal segmentation τ̂ is obtained by minimizing a penalized contrast function J(τ , y)+βpen(τ ). Fo...

This article presents the performance analysis of different segmentation techniques. Global thresholding, Adaptive thresholding, Region grow and Active contour using level set techniques has been used in this paper for proposed segmentation analysis. In this procedure flows as first by Appling segmentation technique to extract ROI from image and calculate the parameters from the resulting image...

In this article we advise to adopt the adaptive technique of acoustic model in the automatic segmentation and labeling of speech corpus. Since the precision of the data segmentation only based on speaker independent model is not good enough, we should transform the speaker independent model into the speaker dependent one. The training method leading to speaker dependent model needs a large amou...

One of the fundamental weaknesses of current computer vision systems used in outdoor applications is their inability to adapt the segmentation process as real-world changes occur in the image. We present a closed loop image segmentation system that incorporates a genetic algorithm to adapt the segmentation process to changes in image characteristics caused by variable environmental conditions. ...