Segmentation is a process of dividing or splitting the image into homogeneous or continuous regions based on the similarity, Similarity may be pixel value of the whole region is similar in some way etc. Image segmentation basically deals with subdivide the image into meaningful structure. The main focus of image segmentation is to find out the object from the image. Aim of image processing task is to finding the object of pixels from image that somehow similar in nature. For example, if we want to find out the length of a car from an image then first we find out the set of pixels that represent the car. Another example in segmentation of medical imaging is to calculate the volume of heart ventricle, so first we find the pixels that make the ventricle. The main goal of image segmentation is to make simpler or to change the representation of an image into different that is more suitable or useful and easily to modify or can perform operation easily. Segmentation is an important process in many image processing and computer vision application. In computer vision, segmentation is a method of divide the whole digital image into several regions. Basically segmentation algorithms are mainly based on the one of the following properties. • Discontinuity • Similarity Discontinuity Discontinuity refers to the unexpected change in the intensity value of pixels. Similarity Similarity refers to partition the image into different-different region based on predefined criteria such as Thresholding , region merging, region growing and region splitting etc. There are several main image segmentation approaches are available. • Region based segmentation • Boundaries detection based segmentation • Pixel based segmentation • Edge based segmentation... ... middle of paper ... ...he image processing, there are many research has been done in this field but we cannot sure that which of the segmentation process are effective than other. There also a tough task to say a particular method or algorithm is applicable to an image or set of image or not. In present era, a commonly used method is subjective evaluation for a segment that evaluates the segmented method. In subjective segmentation evaluation we manually compare the result of different-different segmentation algorithm. This method are effective but more time overshadowing because to judge all methods manually is take too much time. So this method is limited to some methods. Because every person have its own evaluation criteria or its own standard to judge the segment, the result of subjective evaluation method are differs from person to person. So this method can’t give impartial result.
The two were alike in many aspects as described above, but had some dissimilarity as well which are summed up as:
The K-Means algorithm is used for cluster analysis by dividing data points into k clusters. The K means algorithm will group the data into the cluster based on feature similarity.
by the internal computers of the instrument, to create an image of internal body tissues. These images were then displayed on the screen for the user,
the mean value and the standard deviation, to represent the global characteristics of the image, and the image bitmap is used to represent the local characteristics of the image for increasing the accuracy of the retrieval system. Aptoula et al. [8] presen...
...io lateral oblique (MLO)) of the same breast, and same view mammograms were taken at different times. Unsupervised segmentation using a single view can in turn be categorized into six classes, region-based segmentation, contour-based segmentation, clustering segmentation, pseudo-color segmentation, graph segmentation, and variant-feature transformation.
So, the reason for the study of visual crowding is because it can increase our knowledge on object recognition processes for example, feature integration. (Levi, (2008)
Segmentation is the process of identifying different macro-groups of customers (i.e. segments) based on their common characteristics. The process of choosing a target segment, on which to focus marketing activities on, is a process named targeting.
Different parts of images are stored in "layers" so each part can be manipulated without changing the rest. You can, for example, add text on a layer then resize, paint, or remove the text without damaging the picture stored on a different layer. Click this tab to see the various layers in the image. (Note that most images will start with a single background layer only.)
Some places are similar in multiple ways for example both Costa Rica and Washington have similar climate.But, both are also extremely different as well both have different culture and animals.Everything is different one way or another though. This a small difference in the two is Costa Rica has sulfur pit and Washington does not have sulfur pits. Both places are know for the people that come and visit the national parks and the monuments.
Computer vision and human perception – two realizations of the process of seeing, one embedded in computers and the other in people. Clearly there is a metaphorical level in which these two activities have much in common. But is it only a metaphorical level, with fundamental differences always keeping them separate? Or is there a real factor to the metaphor, so that each side could benefit from interacting with the other. To impose a fact that one is better than another is inconceivable as these topics cannot be unparalleled without a train of thought. The process of vision is an immensely complex one that deals with numerous of different theories. At which the visual system of the central nervous gives organisms the ability to process visual detail, as well as enabling the formation of several non-image photo response functions. The process of computer vision is on another scale. “The central nervous system of the computer need to indicate four points: (1) that at which the nature of the computation is expressed; (2) that at which the algorithms that implement a computation are characterized; (3) that at which an algorithm is committed to particular mechanisms; and (4) that are which the mechanisms are realized in hardware.” To reference to computer vision, the software “Pixcavator” illustrates the boundaries of what human perception is capable of in reference to computer vision. The evolving technology of computer vision can interact with human perception to conspire depths that were otherwise not possible.
Segmentation is the process of determining the breakdown of the target market into smaller specific variables that make it easier to evaluate. Gabbott M (2004, p 159) describes the consumer related segmentation variables as being Geodemographic, Psychographic and Behavioural.
Thirdly, the edge points must be well localized, that is, the distance between the edge pixels found by the detector and the actual edge must be minimum. And lastly, only one response must be there for a single edge. The standard convolution method is performed once the mask is calculated. Since the convolution mask is usually much smaller than the actual image, the mask slides over the image, manipulating the pixels in the image.
Segmentation is a marketing strategy that involves separating a wide target market into small groups of customers who share the common need of using or purchasing the product that needs to be marketed. Market segmentation strategies are utilized to identify these groups of consumers and strategies are designed and implemented to make the product or service appeal to them. Support and also the product will be strategically placed in order to successfully achieve the ultimate marketing goal. Businesses and organizations may come up with different type of strategies involving different products and catchy phrases depending on the product or the target segment.
Prior knowledge plays a pivotal role in every aspect of human life. Knowledge can be stored in various formats like images, features, statistical patterns, all these formats help in making sense of the environment. Using prior knowledge humans can perform various activities including, but not limited to: focusing attention, organizing information in to groups, categorizing objects around, hypothesizing, understanding language, and generating inferences(Smith & Kosslyn, 2007). Processing of information is influenced by prior knowledge during the top down processing. Once signal has been detected by the biological visual system, we try to infer meaning using the prior related knowledge which has been stored in the long term memory based on category, association and similarity in features and statistical patterns(Wickens, Lee, Liu, & Becker, 2004). Prior knowledge has no boundaries and it keeps on changing based on experience with the environment making it easier for us humans to understand our surrounding better and quicker as time passes.
Before the discovery of X-rays in 1895, it was impossible to look inside human body, without causing harmful side effects. The famous quote of Anna Bertha Ludwig - “I have seen my death” is a testimony to this. In ancient times, the only way to study internal human organs was the dissection of dead bodies. Additionally, this was also subject to availability or religious beliefs. Leonardo da Vinci made 240 detailed sketches between 1510 and 1511, which were way ahead of their time. Unfortunately, it could not be published, except for a small amount in 1632. Images aide in visualization of illnesses (e.g. a malignant tumor), which are impossible to observe from outside of the body. A surgeon must know the various attributes of the tumor like location and size, before she can operate on it. Similarly an oncologist needs this information to decide the course of treatment e.g. tumor size and metabolic activity may be needed to determine the number of chemotherapy sessions. With images, all this information can be obtained without cutting open the patient. And what’s remarkable is that u...