Abstract: One image is worth more than thousand words.
Images if analyzed can reveal useful information. Low level image
processing deals with the extraction of specific feature from a single
image. Now the question arises: What technique should be used to
extract patterns of very large and detailed image database? The
answer of the question is: “Image Mining”. Image Mining deals with
the extraction of image data relationship, implicit knowledge, and
another pattern from the collection of images or image database. It is
nothing but the extension of Data Mining. In the following paper, not
only we are going to scrutinize the current techniques of image
mining but also present a new technique for mining images using
Genetic Algorithm.
Abstract: An algorithm is a well-defined procedure that takes
some input in the form of some values, processes them and gives the
desired output. It forms the basis of many other algorithms such as
searching, pattern matching, digital filters etc., and other applications
have been found in database systems, data statistics and processing,
data communications and pattern matching. This paper introduces
algorithmic “Enhanced Bidirectional Selection” sort which is
bidirectional, stable. It is said to be bidirectional as it selects two
values smallest from the front and largest from the rear and assigns
them to their appropriate locations thus reducing the number of
passes by half the total number of elements as compared to selection
sort.